Statistical framework for estimating GNSS bias
Vierinen, Juha; Rideout, William C; Erickson, Philip J; Norberg, Johannes
2015-01-01
We present a statistical framework for estimating global navigation satellite system (GNSS) non-ionospheric differential time delay bias. The biases are estimated by examining differences of measured line integrated electron densities (TEC) that are scaled to equivalent vertical integrated densities. The spatio-temporal variability, instrumentation dependent errors, and errors due to inaccurate ionospheric altitude profile assumptions are modeled as structure functions. These structure functions determine how the TEC differences are weighted in the linear least-squares minimization procedure, which is used to produce the bias estimates. A method for automatic detection and removal of outlier measurements that do not fit into a model of receiver bias is also described. The same statistical framework can be used for a single receiver station, but it also scales to a large global network of receivers. In addition to the Global Positioning System (GPS), the method is also applicable to other dual frequency GNSS s...
Statistical framework for estimating GNSS bias
Vierinen, Juha; Coster, Anthea J.; Rideout, William C.; Erickson, Philip J.; Norberg, Johannes
2016-03-01
We present a statistical framework for estimating global navigation satellite system (GNSS) non-ionospheric differential time delay bias. The biases are estimated by examining differences of measured line-integrated electron densities (total electron content: TEC) that are scaled to equivalent vertical integrated densities. The spatiotemporal variability, instrumentation-dependent errors, and errors due to inaccurate ionospheric altitude profile assumptions are modeled as structure functions. These structure functions determine how the TEC differences are weighted in the linear least-squares minimization procedure, which is used to produce the bias estimates. A method for automatic detection and removal of outlier measurements that do not fit into a model of receiver bias is also described. The same statistical framework can be used for a single receiver station, but it also scales to a large global network of receivers. In addition to the Global Positioning System (GPS), the method is also applicable to other dual-frequency GNSS systems, such as GLONASS (Globalnaya Navigazionnaya Sputnikovaya Sistema). The use of the framework is demonstrated in practice through several examples. A specific implementation of the methods presented here is used to compute GPS receiver biases for measurements in the MIT Haystack Madrigal distributed database system. Results of the new algorithm are compared with the current MIT Haystack Observatory MAPGPS (MIT Automated Processing of GPS) bias determination algorithm. The new method is found to produce estimates of receiver bias that have reduced day-to-day variability and more consistent coincident vertical TEC values.
Statistical bias in material decomposition in low photon statistics region
Rajbhandary, Paurakh L.; Pelc, Norbert J.
2015-03-01
We show that in material decomposition, statistical bias exists in the low photon regime due to non-linearity including but not limited to the log operation and polychromatic measurements. As new scan methods divide the total number of photons into an increasing number of measurements (e.g., energy bins, projection paths) and as developers seek to reduce radiation dose, the number of photons per measurement will decrease and estimators should be robust against bias at low photon counts. We study bias as a function of total flux and spectral spread, which provides insight when parameters like material thicknesses, number of energy bins, and number of projection views change. We find that the bias increases with lower photon counts, wide spectrum, with more number of energy bins and more projection views. Our simulation, with ideal photon counting detectors, show biases up to 2.4 % in basis material images. We propose a bias correction method in projection space that uses a multi dimensional look up table. With the correction, the relative bias in CT images is within 0.5 ± 0.17%.
Parametric study of statistical bias in laser Doppler velocimetry
International Nuclear Information System (INIS)
Analytical studies have often assumed that LDV velocity bias depends on turbulence intensity in conjunction with one or more characteristic time scales, such as the time between validated signals, the time between data samples, and the integral turbulence time-scale. These parameters are presently varied independently, in an effort to quantify the biasing effect. Neither of the post facto correction methods employed is entirely accurate. The mean velocity bias error is found to be nearly independent of data validation rate. 15 refs
Beyond Kaiser bias: mildly non-linear two-point statistics of densities in distant spheres
Uhlemann, C.; Codis, S; Kim, J.; Pichon, C.; Bernardeau, F.; Pogosyan, D; Park, C.; L'Huillier, B.
2016-01-01
Simple parameter-free analytic bias functions for the two-point correlation of densities in spheres at large separation are presented. These bias functions generalize the so-called Kaiser bias to the mildly non-linear regime for arbitrary density contrasts. The derivation is carried out in the context of large deviation statistics while relying on the spherical collapse model. A logarithmic transformation provides a saddle approximation which is valid for the whole range of densities and show...
Time-domain Statistics of the Electromagnetic Bias in GNSS-Reflectometry
Directory of Open Access Journals (Sweden)
Ali Ghavidel
2015-08-01
Full Text Available Global Navigation Satellite Systems-Reflectometry (GNSS-R is an emerging remote sensing technique that uses navigation signals reflected on the Earth’s surface as sources of opportunity for scatterometry and altimetry. The time-domain statistics of the electromagnetic bias in GNSS-R altimetry are investigated to assess the residual electromagnetic bias after averaging during the dwell time (as long as 100 s. A three-dimensional time-evolving sea surface is generated using Elfouhaily’s ocean surface height spectrum and spreading function. This surface is illuminated by a right hand circular polarization electromagnetic wave at L-band. Then, the scattered waves are computed using the Physical Optics method under the Kirchhoff Approximation. The electromagnetic bias is estimated using a numerical technique previously validated at C- and Ku-bands, and then extrapolated at L-band. Montecarlo simulations for different sea surface realizations consecutive in time are performed so as to analyze the electromagnetic bias statistics up to the 4PthP order moments. Histograms and distribution of the time domain electromagnetic bias are also used for statistical interpretation. All statistical descriptors confirmed that the electromagnetic bias has a non-Gaussian behavior. This study is important to assess the residual electromagnetic bias in future GNSS-R altimetry missions, such as the “GNSS Reflectometry, Radio Occultation and Scatterometry on board the International Space Station” experiment onboard the International Space Station.
Bias in iterative reconstruction of low-statistics PET data: benefits of a resolution model
International Nuclear Information System (INIS)
Iterative image reconstruction methods such as ordered-subset expectation maximization (OSEM) are widely used in PET. Reconstructions via OSEM are however reported to be biased for low-count data. We investigated this and considered the impact for dynamic PET. Patient listmode data were acquired in [11C]DASB and [15O]H2O scans on the HRRT brain PET scanner. These data were subsampled to create many independent, low-count replicates. The data were reconstructed and the images from low-count data were compared to the high-count originals (from the same reconstruction method). This comparison enabled low-statistics bias to be calculated for the given reconstruction, as a function of the noise-equivalent counts (NEC). Two iterative reconstruction methods were tested, one with and one without an image-based resolution model (RM). Significant bias was observed when reconstructing data of low statistical quality, for both subsampled human and simulated data. For human data, this bias was substantially reduced by including a RM. For [11C]DASB the low-statistics bias in the caudate head at 1.7 M NEC (approx. 30 s) was -5.5% and -13% with and without RM, respectively. We predicted biases in the binding potential of -4% and -10%. For quantification of cerebral blood flow for the whole-brain grey- or white-matter, using [15O]H2O and the PET autoradiographic method, a low-statistics bias of <2.5% and <4% was predicted for reconstruction with and without the RM. The use of a resolution model reduces low-statistics bias and can hence be beneficial for quantitative dynamic PET.
Improving uncertainty estimation in urban hydrological modeling by statistically describing bias
Directory of Open Access Journals (Sweden)
D. Del Giudice
2013-04-01
Full Text Available Hydrodynamic models are useful tools for urban water management. Unfortunately, it is still challenging to obtain accurate results and plausible uncertainty estimates when using these models. In particular, with the currently applied statistical techniques, flow predictions are usually overconfident and biased. In this study, we present a flexible and computationally efficient methodology (i to obtain more reliable hydrological simulations in terms of coverage of validation data by the uncertainty bands and (ii to separate prediction uncertainty into its components. Our approach acknowledges that urban drainage predictions are biased. This is mostly due to input errors and structural deficits of the model. We address this issue by describing model bias in a Bayesian framework. The bias becomes an autoregressive term additional to white measurement noise, the only error type accounted for in traditional uncertainty analysis in urban hydrology. To allow for bigger discrepancies during wet weather, we make the variance of bias dependent on the input (rainfall or/and output (runoff of the system. Specifically, we present a structured approach to select, among five variants, the optimal bias description for a given urban or natural case study. We tested the methodology in a small monitored stormwater system described by means of a parsimonious model. Our results clearly show that flow simulations are much more reliable when bias is accounted for than when it is neglected. Furthermore, our probabilistic predictions can discriminate between three uncertainty contributions: parametric uncertainty, bias (due to input and structural errors, and measurement errors. In our case study, the best performing bias description was the output-dependent bias using a log-sinh transformation of data and model results. The limitations of the framework presented are some ambiguity due to the subjective choice of priors for bias parameters and its inability to directly
Statistical Characterization and Mitigation of NLOS Bias in UWB Localization Systems
Montorsi, Francesco; Vitetta, Giorgio M
2012-01-01
Propagation in non-line-of-sight (NLOS) conditions is one of the major impairments in ultrawideband (UWB) wireless localization systems based on time-of-arrival (TOA) measurements. In this paper the problem of the joint statistical characterization of the NLOS bias and of the most representative features of LOS/NLOS UWB waveforms is investigated. In addition, the performance of various maximum-likelihood (ML) estimators for joint localization and NLOS bias mitigation is assessed. Our numerical results evidence that the accuracy of all the considered estimators is appreciably influenced by the LOS/NLOS conditions of the propagation environment and that a statistical knowledge of multiple signal features can be exploited to mitigate the NLOS bias, reducing the overall localization error.
Beyond Kaiser bias: mildly non-linear two-point statistics of densities in distant spheres
Uhlemann, C; Kim, J; Pichon, C; Bernardeau, F; Pogosyan, D; Park, C; L'Huillier, B
2016-01-01
Simple parameter-free analytic bias functions for the two-point correlation of densities in spheres at large separation are presented. These bias functions generalize the so-called Kaiser bias to the mildly non-linear regime for arbitrary density contrasts. The derivation is carried out in the context of large deviation statistics while relying on the spherical collapse model. A logarithmic transformation provides a saddle approximation which is valid for the whole range of densities and shown to be accurate against the 30 Gpc cube state-of-the-art Horizon Run 4 simulation. Special configurations of two concentric spheres that allow to identify peaks are employed to obtain the conditional bias and a proxy to BBKS extrema correlation functions. These analytic bias functions should be used jointly with extended perturbation theory to predict two-point clustering statistics as they capture the non-linear regime of structure formation at the percent level down to scales of about 10 Mpc/h at redshift 0. Conversely...
Photiadou, Christiana; van den Hurk, Bart; van Delden, Aarnout; Weerts, Albrecht
2016-01-01
An adapted statistical bias correction method is introduced to incorporate circulation-dependence of the model precipitation bias, and its influence on estimated discharges for the Rhine basin is analyzed for a historical period. The bias correction method is tailored to time scales relevant to flooding events in the basin. Large-scale circulation patterns (CPs) are obtained through Maximum Covariance Analysis using reanalysis sea level pressure and high-resolution precipitation observations. A bias correction using these CPs is applied to winter and summer separately, acknowledging the seasonal variability of the circulation regimes in North Europe and their correlation with regional precipitation rates over the Rhine basin. Two different climate model ensemble outputs are explored: ESSENCE and CMIP5. The results of the CP-method are then compared to observations and uncorrected model outputs. Results from a simple bias correction based on a delta factor (NoCP-method) are also used for comparison. For both summer and winter, the CP-method offers a statistically significant improvement of precipitation statistics for subsets of data dominated by particular circulation regimes, demonstrating the circulation-dependence of the precipitation bias. Uncorrected, CP and NoCP corrected model outputs were used as forcing to a hydrological model to simulate river discharges. The CP-method leads to a larger improvement in simulated discharge in the Alpine area in winter than in summer due to a stronger dependence of Rhine precipitation on atmospheric circulation in winter. However, the NoCP-method, in comparison to the CP-method, improves the discharge estimations over the entire Rhine basin.
Bias Expansion of Spatial Statistics and Approximation of Differenced Lattice Point Counts
Indian Academy of Sciences (India)
Daniel J Nordman; Soumendra N Lahiri
2011-05-01
Investigations of spatial statistics, computed from lattice data in the plane, can lead to a special lattice point counting problem. The statistical goal is to expand the asymptotic expectation or large-sample bias of certain spatial covariance estimators, where this bias typically depends on the shape of a spatial sampling region. In particular, such bias expansions often require approximating a difference between two lattice point counts, where the counts correspond to a set of increasing domain (i.e., the sampling region) and an intersection of this set with a vector translate of itself. Non-trivially, the approximation error needs to be of smaller order than the spatial region’s perimeter length. For all convex regions in 2-dimensional Euclidean space and certain unions of convex sets, we show that a difference in areas can approximate a difference in lattice point counts to this required accuracy, even though area can poorly measure the lattice point count of any single set involved in the difference. When investigating large-sample properties of spatial estimators, this approximation result facilitates direct calculation of limiting bias, because, unlike counts, differences in areas are often tractable to compute even with non-rectangular regions. We illustrate the counting approximations with two statistical examples.
Ray, Robert L
2016-01-01
Two-particle correlation measurements and analysis are an important component of the relativistic heavy-ion physics program. In particular, particle pair-number correlations on two-dimensional transverse momentum ($p_t$) allow unique access to soft, semi-hard and hard-scattering processes in these collisions. Precise measurements of this type of correlation are essential for understanding the dynamics in heavy-ion collisions. However, transverse momentum correlation measurements are especially vulnerable to statistical and systematic biases. In this paper the origins of these large bias effects are explained and mathematical correlation forms are derived from mean-$p_t$ fluctuation quantities in the literature in an effort to minimize bias. Monte Carlo simulations are then used to test the degree to which each correlation definition leads to unbiased results in realistic applications. Several correlation forms are shown to be unacceptable for data analysis applications while several others are shown to reprod...
Impact of Baryonic Processes on Weak Lensing Cosmology: Higher-Order Statistics and Parameter Bias
Osato, Ken; Yoshida, Naoki
2015-01-01
We study the impact of baryonic physics on cosmological parameter estimation with weak lensing surveys. We run a set of cosmological hydrodynamics simulations with different galaxy formation models. We then perform ray-tracing simulations through the total matter density field to generate 100 independent convergence maps of 25 deg$^2$ field-of-view, and use them to examine the ability of the following three lensing statistics as cosmological probes; power spectrum, peak counts, and Minkowski Functionals. For the upcoming wide-field observations such as Subaru Hyper Suprime-Cam (HSC) survey with a sky coverage of 1400 deg$^2$, the higher-order statistics provide tight constraints on the matter density, density fluctuation amplitude, and dark energy equation of state, but appreciable parameter bias is induced by the baryonic processes such as gas cooling and stellar feedback. When we use power spectrum, peak counts, and Minkowski Functionals, the relative bias in the dark energy equation of state parameter $w$ ...
Zhang, Zhang
2012-03-22
Background: Genetic mutation, selective pressure for translational efficiency and accuracy, level of gene expression, and protein function through natural selection are all believed to lead to codon usage bias (CUB). Therefore, informative measurement of CUB is of fundamental importance to making inferences regarding gene function and genome evolution. However, extant measures of CUB have not fully accounted for the quantitative effect of background nucleotide composition and have not statistically evaluated the significance of CUB in sequence analysis.Results: Here we propose a novel measure--Codon Deviation Coefficient (CDC)--that provides an informative measurement of CUB and its statistical significance without requiring any prior knowledge. Unlike previous measures, CDC estimates CUB by accounting for background nucleotide compositions tailored to codon positions and adopts the bootstrapping to assess the statistical significance of CUB for any given sequence. We evaluate CDC by examining its effectiveness on simulated sequences and empirical data and show that CDC outperforms extant measures by achieving a more informative estimation of CUB and its statistical significance.Conclusions: As validated by both simulated and empirical data, CDC provides a highly informative quantification of CUB and its statistical significance, useful for determining comparative magnitudes and patterns of biased codon usage for genes or genomes with diverse sequence compositions. 2012 Zhang et al; licensee BioMed Central Ltd.
Directory of Open Access Journals (Sweden)
Zhang Zhang
2012-03-01
Full Text Available Abstract Background Genetic mutation, selective pressure for translational efficiency and accuracy, level of gene expression, and protein function through natural selection are all believed to lead to codon usage bias (CUB. Therefore, informative measurement of CUB is of fundamental importance to making inferences regarding gene function and genome evolution. However, extant measures of CUB have not fully accounted for the quantitative effect of background nucleotide composition and have not statistically evaluated the significance of CUB in sequence analysis. Results Here we propose a novel measure--Codon Deviation Coefficient (CDC--that provides an informative measurement of CUB and its statistical significance without requiring any prior knowledge. Unlike previous measures, CDC estimates CUB by accounting for background nucleotide compositions tailored to codon positions and adopts the bootstrapping to assess the statistical significance of CUB for any given sequence. We evaluate CDC by examining its effectiveness on simulated sequences and empirical data and show that CDC outperforms extant measures by achieving a more informative estimation of CUB and its statistical significance. Conclusions As validated by both simulated and empirical data, CDC provides a highly informative quantification of CUB and its statistical significance, useful for determining comparative magnitudes and patterns of biased codon usage for genes or genomes with diverse sequence compositions.
Um, Myoung-Jin; Kim, Hanbeen; Heo, Jun-Haeng
2016-08-01
A general circulation model (GCM) can be applied to project future climate factors, such as precipitation and atmospheric temperature, to study hydrological and environmental climate change. Although many improvements in GCMs have been proposed recently, projected climate data are still required to be corrected for the biases in generating data before applying the model to practical applications. In this study, a new hybrid process was proposed, and its ability to perform bias correction for the prediction of annual precipitation and annual daily maxima, was tested. The hybrid process in this study was based on quantile mapping with the gamma and generalized extreme value (GEV) distributions and a spline technique to correct the bias of projected daily precipitation. The observed and projected daily precipitation values from the selected stations were analyzed using three bias correction methods, namely, linear scaling, quantile mapping, and hybrid methods. The performances of these methods were analyzed to find the optimal method for prediction of annual precipitation and annual daily maxima. The linear scaling method yielded the best results for estimating the annual average precipitation, while the hybrid method was optimal for predicting the variation in annual precipitation. The hybrid method described the statistical characteristics of the annual maximum series (AMS) similarly to the observed data. In addition, this method demonstrated the lowest root mean squared error (RMSE) and the highest coefficient of determination (R2) for predicting the quantiles of the AMS for the extreme value analysis of precipitation.
Greenberg, Ariela Caren
Differential item functioning (DIF) and differential distractor functioning (DDF) are methods used to screen for item bias (Camilli & Shepard, 1994; Penfield, 2008). Using an applied empirical example, this mixed-methods study examined the congruency and relationship of DIF and DDF methods in screening multiple-choice items. Data for Study I were drawn from item responses of 271 female and 236 male low-income children on a preschool science assessment. Item analyses employed a common statistical approach of the Mantel-Haenszel log-odds ratio (MH-LOR) to detect DIF in dichotomously scored items (Holland & Thayer, 1988), and extended the approach to identify DDF (Penfield, 2008). Findings demonstrated that the using MH-LOR to detect DIF and DDF supported the theoretical relationship that the magnitude and form of DIF and are dependent on the DDF effects, and demonstrated the advantages of studying DIF and DDF in multiple-choice items. A total of 4 items with DIF and DDF and 5 items with only DDF were detected. Study II incorporated an item content review, an important but often overlooked and under-published step of DIF and DDF studies (Camilli & Shepard). Interviews with 25 female and 22 male low-income preschool children and an expert review helped to interpret the DIF and DDF results and their comparison, and determined that a content review process of studied items can reveal reasons for potential item bias that are often congruent with the statistical results. Patterns emerged and are discussed in detail. The quantitative and qualitative analyses were conducted in an applied framework of examining the validity of the preschool science assessment scores for evaluating science programs serving low-income children, however, the techniques can be generalized for use with measures across various disciplines of research.
DEFF Research Database (Denmark)
Thorson, James T.; Kristensen, Kasper
2016-01-01
Statistical models play an important role in fisheries science when reconciling ecological theory with available data for wild populations or experimental studies. Ecological models increasingly include both fixed and random effects, and are often estimated using maximum likelihood techniques...... is calculated as a nonlinear function of random effects. We therefore describe and evaluate a new "epsilon" estimator as a generic bias-correction estimator for derived quantities. We use simulated data to compare the epsilon-method with an existing bias-correction algorithm for estimating...... recruitment in four configurations of an age-structured population dynamics model. This simulation experiment shows that the epsilon-method and the existing bias-correction method perform equally well in data-rich contexts, but the epsilon-method is slightly less biased in data-poor contexts. We then apply...
A statistical characterization of the Galileo-to-GPS inter-system bias
Gioia, Ciro; Borio, Daniele
2016-06-01
Global navigation satellite system operates using independent time scales and thus inter-system time offsets have to be determined to enable multi-constellation navigation solutions. GPS/Galileo inter-system bias and drift are evaluated here using different types of receivers: two mass market and two professional receivers. Moreover, three different approaches are considered for the inter-system bias determination: in the first one, the broadcast Galileo to GPS time offset is used to align GPS and Galileo time scales. In the second, the inter-system bias is included in the multi-constellation navigation solution and is estimated using the measurements available. Finally, an enhanced algorithm using constraints on the inter-system bias time evolution is proposed. The inter-system bias estimates obtained with the different approaches are analysed and their stability is experimentally evaluated using the Allan deviation. The impact of the inter-system bias on the position velocity time solution is also considered and the performance of the approaches analysed is evaluated in terms of standard deviation and mean errors for both horizontal and vertical components. From the experiments, it emerges that the inter-system bias is very stable and that the use of constraints, modelling the GPS/Galileo inter-system bias behaviour, significantly improves the performance of multi-constellation navigation.
Directory of Open Access Journals (Sweden)
R. Rojas
2011-08-01
Full Text Available In this work we asses the benefits of removing bias in climate forcing data used for hydrological climate change impact assessment at pan-European scale, with emphasis on floods. Climate simulations from the HIRHAM5-ECHAM5 model driven by the SRES-A1B emission scenario are corrected for bias using a histogram equalization method. As target for the bias correction we employ gridded interpolated observations of precipitation, average, minimum, and maximum temperature from the E-OBS data set. Bias removal transfer functions are derived for the control period 1961–1990. These are subsequently used to correct the climate simulations for the control period, and, under the assumption of a stationary error model, for the future time window 2071–2100. Validation against E-OBS climatology in the control period shows that the correction method performs successfully in removing bias in average and extreme statistics relevant for flood simulation over the majority of the European domain in all seasons. This translates into considerably improved simulations with the hydrological model of observed average and extreme river discharges at a majority of 554 validation river stations across Europe. Probabilities of extreme events derived employing extreme value techniques are also more closely reproduced. Results indicate that projections of future flood hazard in Europe based on uncorrected climate simulations, both in terms of their magnitude and recurrence interval, are likely subject to large errors. Notwithstanding the inherent limitations of the large-scale approach used herein, this study strongly advocates the removal of bias in climate simulations prior to their use in hydrological impact assessment.
Sereno, Mauro; Ettori, Stefano; Moscardini, Lauro
2014-01-01
The relation between mass and concentration of galaxy clusters traces their formation and evolution. Massive lensing clusters were observed to be over-concentrated and following a steeper scaling in tension with predictions from the standard concordance $\\Lambda$CDM paradigm. We critically revise the relation in the CLASH, the SGAS, the LOCUSS and a high-redshift samples of weak lensing clusters. Measurements of mass and concentration are anti-correlated, which can bias the observed relation towards steeper values. We corrected for this bias and compared the measured relation to theoretical predictions accounting for halo triaxiality, adiabatic contraction of the halo, presence of a dominant BCG and, mostly, selection effects in the observed sample. The normalization, the slope and the scatter of the expected relation are strongly sample-dependent. For the considered samples, the predicted slope is much steeper than that of the underlying relation characterizing dark-matter only clusters. We found that correc...
Zhang Zhang; Li Jun; Cui Peng; Ding Feng; Li Ang; Townsend Jeffrey P; Yu Jun
2012-01-01
Abstract Background Genetic mutation, selective pressure for translational efficiency and accuracy, level of gene expression, and protein function through natural selection are all believed to lead to codon usage bias (CUB). Therefore, informative measurement of CUB is of fundamental importance to making inferences regarding gene function and genome evolution. However, extant measures of CUB have not fully accounted for the quantitative effect of background nucleotide composition and have not...
How cognitive biases can distort environmental statistics: introducing the rough estimation task.
Wilcockson, Thomas D W; Pothos, Emmanuel M
2016-04-01
The purpose of this study was to develop a novel behavioural method to explore cognitive biases. The task, called the Rough Estimation Task, simply involves presenting participants with a list of words that can be in one of three categories: appetitive words (e.g. alcohol, food, etc.), neutral related words (e.g. musical instruments) and neutral unrelated words. Participants read the words and are then asked to state estimates for the percentage of words in each category. Individual differences in the propensity to overestimate the proportion of appetitive stimuli (alcohol-related or food-related words) in a word list were associated with behavioural measures (i.e. alcohol consumption, hazardous drinking, BMI, external eating and restrained eating, respectively), thereby providing evidence for the validity of the task. The task was also found to be associated with an eye-tracking attentional bias measure. The Rough Estimation Task is motivated in relation to intuitions with regard to both the behaviour of interest and the theory of cognitive biases in substance use. PMID:26866972
International Nuclear Information System (INIS)
External linking scripts between Monte Carlo transport codes and burnup codes, and complete integration of burnup capability into Monte Carlo transport codes, have been or are currently being developed. Monte Carlo linked burnup methodologies may serve as an excellent benchmark for new deterministic burnup codes used for advanced systems; however, there are some instances where deterministic methodologies break down (i.e., heavily angularly biased systems containing exotic materials without proper group structure) and Monte Carlo burn up may serve as an actual design tool. Therefore, researchers are also developing these capabilities in order to examine complex, three-dimensional exotic material systems that do not contain benchmark data. Providing a reference scheme implies being able to associate statistical errors to any neutronic value of interest like k(eff), reaction rates, fluxes, etc. Usually in Monte Carlo, standard deviations are associated with a particular value by performing different independent and identical simulations (also referred to as 'cycles', 'batches', or 'replicas'), but this is only valid if the calculation itself is not biased. And, as will be shown in this paper, there is a bias in the methodology that consists of coupling transport and depletion codes because Bateman equations are not linear functions of the fluxes or of the reaction rates (those quantities being always measured with an uncertainty). Therefore, we have to quantify and correct this bias. This will be achieved by deriving an unbiased minimum variance estimator of a matrix exponential function of a normal mean. The result is then used to propose a reference scheme to solve Boltzmann/Bateman coupled equations, thanks to Monte Carlo transport codes. Numerical tests will be performed with an ad hoc Monte Carlo code on a very simple depletion case and will be compared to the theoretical results obtained with the reference scheme. Finally, the statistical error propagation
Dagnall, Neil; Denovan, Andrew; Drinkwater, Kenneth; Parker, Andrew; Clough, Peter
2016-01-01
The present paper examined relationships between schizotypy (measured by the Oxford-Liverpool Inventory of Feelings and Experience; O-LIFE scale brief), belief in the paranormal (assessed via the Revised Paranormal Belief Scale; RPBS) and proneness to statistical bias (i.e., perception of randomness and susceptibility to conjunction fallacy). Participants were 254 volunteers recruited via convenience sampling. Probabilistic reasoning problems appeared framed within both standard and paranormal contexts. Analysis revealed positive correlations between the Unusual Experience (UnExp) subscale of O-LIFE and paranormal belief measures [RPBS full scale, traditional paranormal beliefs (TPB) and new age philosophy]. Performance on standard problems correlated negatively with UnExp and belief in the paranormal (particularly the TPB dimension of the RPBS). Consideration of specific problem types revealed that perception of randomness associated more strongly with belief in the paranormal than conjunction; both problem types related similarly to UnExp. Structural equation modeling specified that belief in the paranormal mediated the indirect relationship between UnExp and statistical bias. For problems presented in a paranormal context a framing effect occurred. Whilst UnExp correlated positively with conjunction proneness (controlling for perception of randomness), there was no association between UnExp and perception of randomness (controlling for conjunction). PMID:27471481
Statistical characterization of voltage-biased SQUIDs with weakly damped junctions
International Nuclear Information System (INIS)
Recently, it has been shown that voltage-biased readout of SQUIDs with weakly damped junctions (large Stewart–McCumber parameter βc, due to high shunt resistance) is useful for suppression of preamplifier noise. We experimentally studied the characteristics of 53 planar niobium–SQUID magnetometers with junction shunt resistors RJ nominally of 30 Ω fabricated on 5 × 5 mm2 chips. The field-to-flux transfer coefficient ∂B/∂Φ of the magnetometers was 1.5 nT/Φ0, with a SQUID loop inductance Ls of about 350 pH. The distributions of important SQUID parameters, such as the current swing Iswing, the dynamic resistance Rd, and the flux-to-voltage transfer coefficient ∂V/∂Φ, are given. Nearly all the SQUIDs could be stably operated in the voltage bias mode and their ∂V/∂Φ reached a large mean value of 380 μV/Φ0. In this case, the SQUIDs can be read out directly by a commercial operational amplifier without any additional means to suppress preamplifier noise. The mean flux noise of the SQUIDs was found to be 4.5 μΦ0 Hz−1/2, corresponding to a field resolution of 7 fT Hz−1/2. To demonstrate the applicability of these SQUIDs in the direct readout scheme, a simple four-channel SQUID gradiometer system was set up to perform magnetocardiography and magnetoencephalography measurements in a magnetically shielded room. (paper)
Kuusela, Mikael
2015-01-01
We consider the high energy physics unfolding problem where the goal is to estimate the spectrum of elementary particles given observations distorted by the limited resolution of a particle detector. This important statistical inverse problem arising in data analysis at the Large Hadron Collider at CERN consists in estimating the intensity function of an indirectly observed Poisson point process. Unfolding typically proceeds in two steps: one first produces a regularized point estimate of the unknown intensity and then uses the variability of this estimator to form frequentist confidence intervals that quantify the uncertainty of the solution. In this paper, we propose forming the point estimate using empirical Bayes estimation which enables a data-driven choice of the regularization strength through marginal maximum likelihood estimation. Observing that neither Bayesian credible intervals nor standard bootstrap confidence intervals succeed in achieving good frequentist coverage in this problem due to the inh...
Li, R.; Wang, S.-Y.; Gillies, R. R.
2016-04-01
Large biases associated with climate projections are problematic when it comes to their regional application in the assessment of water resources and ecosystems. Here, we demonstrate a method that can reduce systematic biases in regional climate projections. The global and regional climate models employed to demonstrate the technique are the Community Climate System Model (CCSM) and the Weather Research and Forecasting (WRF) model. The method first utilized a statistical regression technique and a global reanalysis dataset to correct biases in the CCSM-simulated variables (e.g., temperature, geopotential height, specific humidity, and winds) that are subsequently used to drive the WRF model. The WRF simulations were conducted for the western United States and were driven with (a) global reanalysis, (b) original CCSM, and (c) bias-corrected CCSM data. The bias-corrected CCSM data led to a more realistic regional climate simulation of precipitation and associated atmospheric dynamics, as well as snow water equivalent (SWE), in comparison to the original CCSM-driven WRF simulation. Since most climate applications rely on existing global model output as the forcing data (i.e., they cannot re-run or change the global model), which often contain large biases, this method provides an effective and economical tool to reduce biases in regional climate downscaling simulations of water resource variables.
Indian Academy of Sciences (India)
V R Durai; Rashmi Bhardwaj
2014-07-01
The output from Global Forecasting System (GFS) T574L64 operational at India Meteorological Department (IMD), New Delhi is used for obtaining location specific quantitative forecast of maximum and minimum temperatures over India in the medium range time scale. In this study, a statistical bias correction algorithm has been introduced to reduce the systematic bias in the 24–120 hour GFS model location specific forecast of maximum and minimum temperatures for 98 selected synoptic stations, representing different geographical regions of India. The statistical bias correction algorithm used for minimizing the bias of the next forecast is Decaying Weighted Mean (DWM), as it is suitable for small samples. The main objective of this study is to evaluate the skill of Direct Model Output (DMO) and Bias Corrected (BC) GFS for location specific forecast of maximum and minimum temperatures over India. The performance skill of 24–120 hour DMO and BC forecast of GFS model is evaluated for all the 98 synoptic stations during summer (May–August 2012) and winter (November 2012–February 2013) seasons using different statistical evaluation skill measures. The magnitude of Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) for BC GFS forecast is lower than DMO during both summer and winter seasons. The BC GFS forecasts have higher skill score as compared to GFS DMO over most of the stations in all day-1 to day-5 forecasts during both summer and winter seasons. It is concluded from the study that the skill of GFS statistical BC forecast improves over the GFS DMO remarkably and hence can be used as an operational weather forecasting system for location specific forecast over India.
Baronchelli, Andrea; Loreto, Vittorio; Puglisi, Andrea
2015-01-01
Language universals have long been attributed to an innate Universal Grammar. An alternative explanation states that linguistic universals emerged independently in every language in response to shared cognitive or perceptual biases. A computational model has recently shown how this could be the case, focusing on the paradigmatic example of the universal properties of colour naming patterns, and producing results in quantitative agreement with the experimental data. Here we investigate the role of an individual perceptual bias in the framework of the model. We study how, and to what extent, the structure of the bias influences the corresponding linguistic universal patterns. We show that the cultural history of a group of speakers introduces population-specific constraints that act against the pressure for uniformity arising from the individual bias, and we clarify the interplay between these two forces. PMID:26018391
Casanueva, A.; Kotlarski, S.; Herrera, S.; Fernández, J.; Gutiérrez, J. M.; Boberg, F.; Colette, A.; Christensen, O. B.; Goergen, K.; Jacob, D.; Keuler, K.; Nikulin, G.; Teichmann, C.; Vautard, R.
2015-10-01
Daily precipitation statistics as simulated by the ERA-Interim-driven EURO-CORDEX regional climate model (RCM) ensemble are evaluated over two distinct regions of the European continent, namely the European Alps and Spain. The potential added value of the high-resolution 12 km experiments with respect to their 50 km resolution counterparts is investigated. The statistics considered consist of wet-day intensity and precipitation frequency as a measure of mean precipitation, and three precipitation-derived indicators (90th percentile on wet days—90pWET, contribution of the very wet days to total precipitation—R95pTOT and number of consecutive dry days—CDD). As reference for model evaluation high resolution gridded observational data over continental Spain (Spain011/044) and the Alpine region (EURO4M-APGD) are used. The assessment and comparison of the two resolutions is accomplished not only on their original horizontal grids (approximately 12 and 50 km), but the high-resolution RCMs are additionally regridded onto the coarse 50 km grid by grid cell aggregation for the direct comparison with the low resolution simulations. The direct application of RCMs e.g. in many impact modelling studies is hampered by model biases. Therefore bias correction (BC) techniques are needed at both resolutions to ensure a better agreement between models and observations. In this work, the added value of the high resolution (before and after the bias correction) is assessed and the suitability of these BC methods is also discussed. Three basic BC methods are applied to isolate the effect of biases in mean precipitation, wet-day intensity and wet-day frequency on the derived indicators. Daily precipitation percentiles are strongly affected by biases in the wet-day intensity, whereas the dry spells are better represented when the simulated precipitation frequency is adjusted to the observed one. This confirms that there is no single optimal way to correct for RCM biases, since
Casanueva, A.; Kotlarski, S.; Herrera, S.; Fernández, J.; Gutiérrez, J. M.; Boberg, F.; Colette, A.; Christensen, O. B.; Goergen, K.; Jacob, D.; Keuler, K.; Nikulin, G.; Teichmann, C.; Vautard, R.
2016-08-01
Daily precipitation statistics as simulated by the ERA-Interim-driven EURO-CORDEX regional climate model (RCM) ensemble are evaluated over two distinct regions of the European continent, namely the European Alps and Spain. The potential added value of the high-resolution 12 km experiments with respect to their 50 km resolution counterparts is investigated. The statistics considered consist of wet-day intensity and precipitation frequency as a measure of mean precipitation, and three precipitation-derived indicators (90th percentile on wet days—90pWET, contribution of the very wet days to total precipitation—R95pTOT and number of consecutive dry days—CDD). As reference for model evaluation high resolution gridded observational data over continental Spain (Spain011/044) and the Alpine region (EURO4M-APGD) are used. The assessment and comparison of the two resolutions is accomplished not only on their original horizontal grids (approximately 12 and 50 km), but the high-resolution RCMs are additionally regridded onto the coarse 50 km grid by grid cell aggregation for the direct comparison with the low resolution simulations. The direct application of RCMs e.g. in many impact modelling studies is hampered by model biases. Therefore bias correction (BC) techniques are needed at both resolutions to ensure a better agreement between models and observations. In this work, the added value of the high resolution (before and after the bias correction) is assessed and the suitability of these BC methods is also discussed. Three basic BC methods are applied to isolate the effect of biases in mean precipitation, wet-day intensity and wet-day frequency on the derived indicators. Daily precipitation percentiles are strongly affected by biases in the wet-day intensity, whereas the dry spells are better represented when the simulated precipitation frequency is adjusted to the observed one. This confirms that there is no single optimal way to correct for RCM biases, since
Hayslett, H T
1991-01-01
Statistics covers the basic principles of Statistics. The book starts by tackling the importance and the two kinds of statistics; the presentation of sample data; the definition, illustration and explanation of several measures of location; and the measures of variation. The text then discusses elementary probability, the normal distribution and the normal approximation to the binomial. Testing of statistical hypotheses and tests of hypotheses about the theoretical proportion of successes in a binomial population and about the theoretical mean of a normal population are explained. The text the
Rosenbaum, Paul R
2016-03-01
A common practice with ordered doses of treatment and ordered responses, perhaps recorded in a contingency table with ordered rows and columns, is to cut or remove a cross from the table, leaving the outer corners-that is, the high-versus-low dose, high-versus-low response corners-and from these corners to compute a risk or odds ratio. This little remarked but common practice seems to be motivated by the oldest and most familiar method of sensitivity analysis in observational studies, proposed by Cornfield et al. (1959), which says that to explain a population risk ratio purely as bias from an unobserved binary covariate, the prevalence ratio of the covariate must exceed the risk ratio. Quite often, the largest risk ratio, hence the one least sensitive to bias by this standard, is derived from the corners of the ordered table with the central cross removed. Obviously, the corners use only a portion of the data, so a focus on the corners has consequences for the standard error as well as for bias, but sampling variability was not a consideration in this early and familiar form of sensitivity analysis, where point estimates replaced population parameters. Here, this cross-cut analysis is examined with the aid of design sensitivity and the power of a sensitivity analysis. PMID:26295693
Links to sources of cancer-related statistics, including the Surveillance, Epidemiology and End Results (SEER) Program, SEER-Medicare datasets, cancer survivor prevalence data, and the Cancer Trends Progress Report.
International Nuclear Information System (INIS)
For the year 1999 and 2000, part of the figures shown in the tables of the Energy Review are preliminary or estimated. The annual statistics of the Energy Review appear in more detail from the publication Energiatilastot - Energy Statistics issued annually, which also includes historical time series over a longer period (see e.g., Energiatilastot 1998, Statistics Finland, Helsinki 1999, ISSN 0785-3165). The inside of the Review's back cover shows the energy units and the conversion coefficients used for them. Explanatory notes to the statistical tables can be found after tables and figures. The figures presents: Changes in the volume of GNP and energy consumption, Changes in the volume of GNP and electricity, Coal consumption, Natural gas consumption, Peat consumption, Domestic oil deliveries, Import prices of oil, Consumer prices of principal oil products, Fuel prices for heat production, Fuel prices for electricity production, Carbon dioxide emissions, Total energy consumption by source and CO2-emissions, Electricity supply, Energy imports by country of origin in January-March 2000, Energy exports by recipient country in January-March 2000, Consumer prices of liquid fuels, Consumer prices of hard coal, natural gas and indigenous fuels, Average electricity price by type of consumer, Price of district heating by type of consumer, Excise taxes, value added taxes and fiscal charges and fees included in consumer prices of some energy sources and Energy taxes and precautionary stock fees on oil products
Elvarsson, B. P.; Taylor, L.; Trenkel, Verena; Kupca, V.; Stefansson, G.
2014-01-01
Statistical models of marine ecosystems use a variety of data sources to estimate parameters using composite or weighted likelihood functions with associated weighting issues and questions on how to obtain variance estimates. Regardless of the method used to obtain point estimates, a method is required for variance estimation. A bootstrap technique is introduced for the evaluation of uncertainty in such models, taking into account inherent spatial and temporal correlations in the datasets, wh...
International Nuclear Information System (INIS)
For the year 2002, part of the figures shown in the tables of the Energy Review are partly preliminary. The annual statistics of the Energy Review also includes historical time-series over a longer period (see e.g. Energiatilastot 2001, Statistics Finland, Helsinki 2002). The applied energy units and conversion coefficients are shown in the inside back cover of the Review. Explanatory notes to the statistical tables can be found after tables and figures. The figures presents: Changes in GDP, energy consumption and electricity consumption, Carbon dioxide emissions from fossile fuels use, Coal consumption, Consumption of natural gas, Peat consumption, Domestic oil deliveries, Import prices of oil, Consumer prices of principal oil products, Fuel prices in heat production, Fuel prices in electricity production, Price of electricity by type of consumer, Average monthly spot prices at the Nord pool power exchange, Total energy consumption by source and CO2-emissions, Supply and total consumption of electricity GWh, Energy imports by country of origin in January-June 2003, Energy exports by recipient country in January-June 2003, Consumer prices of liquid fuels, Consumer prices of hard coal, natural gas and indigenous fuels, Price of natural gas by type of consumer, Price of electricity by type of consumer, Price of district heating by type of consumer, Excise taxes, value added taxes and fiscal charges and fees included in consumer prices of some energy sources and Excise taxes, precautionary stock fees on oil pollution fees on energy products
International Nuclear Information System (INIS)
For the year 2003 and 2004, the figures shown in the tables of the Energy Review are partly preliminary. The annual statistics of the Energy Review also includes historical time-series over a longer period (see e.g. Energiatilastot, Statistics Finland, Helsinki 2003, ISSN 0785-3165). The applied energy units and conversion coefficients are shown in the inside back cover of the Review. Explanatory notes to the statistical tables can be found after tables and figures. The figures presents: Changes in GDP, energy consumption and electricity consumption, Carbon dioxide emissions from fossile fuels use, Coal consumption, Consumption of natural gas, Peat consumption, Domestic oil deliveries, Import prices of oil, Consumer prices of principal oil products, Fuel prices in heat production, Fuel prices in electricity production, Price of electricity by type of consumer, Average monthly spot prices at the Nord pool power exchange, Total energy consumption by source and CO2-emissions, Supplies and total consumption of electricity GWh, Energy imports by country of origin in January-March 2004, Energy exports by recipient country in January-March 2004, Consumer prices of liquid fuels, Consumer prices of hard coal, natural gas and indigenous fuels, Price of natural gas by type of consumer, Price of electricity by type of consumer, Price of district heating by type of consumer, Excise taxes, value added taxes and fiscal charges and fees included in consumer prices of some energy sources and Excise taxes, precautionary stock fees on oil pollution fees
Directory of Open Access Journals (Sweden)
Phillips Carl V
2004-08-01
Full Text Available Abstract Background Publication bias, as typically defined, refers to the decreased likelihood of studies' results being published when they are near the null, not statistically significant, or otherwise "less interesting." But choices about how to analyze the data and which results to report create a publication bias within the published results, a bias I label "publication bias in situ" (PBIS. Discussion PBIS may create much greater bias in the literature than traditionally defined publication bias (the failure to publish any result from a study. The causes of PBIS are well known, consisting of various decisions about reporting that are influenced by the data. But its impact is not generally appreciated, and very little attention is devoted to it. What attention there is consists largely of rules for statistical analysis that are impractical and do not actually reduce the bias in reported estimates. PBIS cannot be reduced by statistical tools because it is not fundamentally a problem of statistics, but rather of non-statistical choices and plain language interpretations. PBIS should be recognized as a phenomenon worthy of study – it is extremely common and probably has a huge impact on results reported in the literature – and there should be greater systematic efforts to identify and reduce it. The paper presents examples, including results of a recent HIV vaccine trial, that show how easily PBIS can have a large impact on reported results, as well as how there can be no simple answer to it. Summary PBIS is a major problem, worthy of substantially more attention than it receives. There are ways to reduce the bias, but they are very seldom employed because they are largely unrecognized.
Hewstone, Miles; Rubin, Mark; Willis, Hazel
2002-01-01
This chapter reviews the extensive literature on bias in favor of in-groups at the expense of out-groups. We focus on five issues and identify areas for future research: (a) measurement and conceptual issues (especially in-group favoritism vs. out-group derogation, and explicit vs. implicit measures of bias); (b) modern theories of bias highlighting motivational explanations (social identity, optimal distinctiveness, uncertainty reduction, social dominance, terror management); (c) key moderators of bias, especially those that exacerbate bias (identification, group size, status and power, threat, positive-negative asymmetry, personality and individual differences); (d) reduction of bias (individual vs. intergroup approaches, especially models of social categorization); and (e) the link between intergroup bias and more corrosive forms of social hostility. PMID:11752497
The Probability Distribution for a Biased Spinner
Foster, Colin
2012-01-01
This article advocates biased spinners as an engaging context for statistics students. Calculating the probability of a biased spinner landing on a particular side makes valuable connections between probability and other areas of mathematics. (Contains 2 figures and 1 table.)
Roese, Neal J; Vohs, Kathleen D
2012-09-01
Hindsight bias occurs when people feel that they "knew it all along," that is, when they believe that an event is more predictable after it becomes known than it was before it became known. Hindsight bias embodies any combination of three aspects: memory distortion, beliefs about events' objective likelihoods, or subjective beliefs about one's own prediction abilities. Hindsight bias stems from (a) cognitive inputs (people selectively recall information consistent with what they now know to be true and engage in sensemaking to impose meaning on their own knowledge), (b) metacognitive inputs (the ease with which a past outcome is understood may be misattributed to its assumed prior likelihood), and (c) motivational inputs (people have a need to see the world as orderly and predictable and to avoid being blamed for problems). Consequences of hindsight bias include myopic attention to a single causal understanding of the past (to the neglect of other reasonable explanations) as well as general overconfidence in the certainty of one's judgments. New technologies for visualizing and understanding data sets may have the unintended consequence of heightening hindsight bias, but an intervention that encourages people to consider alternative causal explanations for a given outcome can reduce hindsight bias. PMID:26168501
Venema, Victor; Lindau, Ralf
2016-04-01
In an accompanying talk we show that well-homogenized national dataset warm more than temperatures from global collections averaged over the region of common coverage. In this poster we want to present auxiliary work about possible biases in the raw observations and on how well relative statistical homogenization can remove trend biases. There are several possible causes of cooling biases, which have not been studied much. Siting could be an important factor. Urban stations tend to move away from the centre to better locations. Many stations started inside of urban areas and are nowadays more outside. Even for villages the temperature difference between the centre and edge can be 0.5°C. When a city station moves to an airport, which often happened around WWII, this takes the station (largely) out of the urban heat island. During the 20th century the Stevenson screen was established as the dominant thermometer screen. This screen protected the thermometer much better against radiation than earlier designs. Deficits of earlier measurement methods have artificially warmed the temperatures in the 19th century. Newer studies suggest we may have underestimated the size of this bias. Currently we are in a transition to Automatic Weather Stations. The net global effect of this transition is not clear at this moment. Irrigation on average decreases the 2m-temperature by about 1 degree centigrade. At the same time, irrigation has increased significantly during the last century. People preferentially live in irrigated areas and weather stations serve agriculture. Thus it is possible that there is a higher likelihood that weather stations are erected in irrigated areas than elsewhere. In this case irrigation could lead to a spurious cooling trend. In the Parallel Observations Science Team of the International Surface Temperature Initiative (ISTI-POST) we are studying influence of the introduction of Stevenson screens and Automatic Weather Stations using parallel measurements
Challenges in bias correcting climate change simulations
Maraun, Douglas; Shepherd, Ted; Zappa, Giuseppe; Gutierrez, Jose; Widmann, Martin; Hagemann, Stefan; Richter, Ingo; Soares, Pedro; Mearns, Linda
2016-04-01
Biases in climate model simulations - if these are directly used as input for impact models - will introduce further biases in subsequent impact simulations. In response to this issue, so-called bias correction methods have been developed to post-process climate model output. These methods are now widely used and a crucial component in the generation of high resolution climate change projections. Bias correction is conceptually similar to model output statistics, which has been successfully used for several decades in numerical weather prediction. Yet in climate science, some authors outrightly dismiss any form of bias correction. Starting from this seeming contradiction, we highlight differences between the two contexts and infer consequences and limitations for the applicability of bias correction to climate change projections. We first show that cross validation approaches successfully used to evaluate weather forecasts are fundamentally insufficient to evaluate climate change bias correction. We further demonstrate that different types of model mismatches with observations require different solutions, and some may not sensibly be mitigated. In particular we consider the influence of large-scale circulation biases, biases in the persistence of weather regimes, and regional biases caused by an insufficient representation of the flow-topography interaction. We conclude with a list of recommendations and suggestions for future research to reduce, to post-process, and to cope with climate model biases.
Pope, Devin G.; Price, Joseph; Wolfers, Justin
2014-01-01
Can raising awareness of racial bias subsequently reduce that bias? We address this question by exploiting the widespread media attention highlighting racial bias among professional basketball referees that occurred in May 2007 following the release of an academic study. Using new data, we confirm that racial bias persisted in the years after the study's original sample, but prior to the media coverage. Subsequent to the media coverage though, the bias completely disappeared. We examine poten...
Bias and variance in continuous EDA
Teytaud, Fabien; Teytaud, Olivier
2009-01-01
Estimation of Distribution Algorithms are based on statistical estimates. We show that when combining classical tools from statistics, namely bias/variance decomposition, reweighting and quasi-randomization, we can strongly improve the convergence rate. All modiﬁcations are easy, compliant with most algorithms, and experimentally very eﬃcient in particular in the parallel case (large oﬀsprings).
Generalization of the FRAM's Bias
International Nuclear Information System (INIS)
The Fixed-Energy Response-Function Analysis with Multiple Efficiency (FRAM) code was developed at Los Alamos National Laboratory to measure the gamma-ray spectrometry of the isotopic composition of plutonium, uranium, and other actinides. Its reported uncertainties of the results come from the propagation of the statistics in the peak areas only. No systematic error components are included in the reported uncertainties. We have done several studies and found that the FRAM's statistical precision can be reasonably represented by its reported uncertainties. The FRAM's biases or systematic uncertainties can come from a variety of sources and can be difficult to determine. We carefully examined the FRAM analytical results of the archival plutonium data and of the data specifically acquired for this isotopic uncertainty analysis project and found the relationship between the bias and other parameters. We worked out the equations representing the biases of the measured isotopes from each measurement using the internal parameters in the spectrum such as peak resolution and shape, region of analysis, and burnup (for plutonium) or enrichment (for uranium)
Publication Bias The "File-Drawer Problem" in Scientific Inference
Scargle, J D
1999-01-01
Publication bias arises whenever the probability that a study is published depends on the statistical significance of its results. This bias, often called the file-drawer effect since the unpublished results are imagined to be tucked away in researchers' file cabinets, is potentially a severe impediment to combining the statistical results of studies collected from the literature. With almost any reasonable quantitative model for publication bias, only a small number of studies lost in the file-drawer will produce a significant bias. This result contradicts the well known Fail Safe File Drawer (FSFD) method for setting limits on the potential harm of publication bias, widely used in social, medical and psychic research. This method incorrectly treats the file drawer as unbiased, and almost always misestimates the seriousness of publication bias. A large body of not only psychic research, but medical and social science studies, has mistakenly relied on this method to validate claimed discoveries. Statistical c...
Statistical electromagnetics: Complex cavities
Naus, H.W.L.
2008-01-01
A selection of the literature on the statistical description of electromagnetic fields and complex cavities is concisely reviewed. Some essential concepts, for example, the application of the central limit theorem and the maximum entropy principle, are scrutinized. Implicit assumptions, biased choic
Recursive bias estimation and L2 boosting
Energy Technology Data Exchange (ETDEWEB)
Hengartner, Nicolas W [Los Alamos National Laboratory; Cornillon, Pierre - Andre [INRA, FRANCE; Matzner - Lober, Eric [RENNE, FRANCE
2009-01-01
This paper presents a general iterative bias correction procedure for regression smoothers. This bias reduction schema is shown to correspond operationally to the L{sub 2} Boosting algorithm and provides a new statistical interpretation for L{sub 2} Boosting. We analyze the behavior of the Boosting algorithm applied to common smoothers S which we show depend on the spectrum of I - S. We present examples of common smoother for which Boosting generates a divergent sequence. The statistical interpretation suggest combining algorithm with an appropriate stopping rule for the iterative procedure. Finally we illustrate the practical finite sample performances of the iterative smoother via a simulation study.
Lagrangian bias in the local bias model
International Nuclear Information System (INIS)
It is often assumed that the halo-patch fluctuation field can be written as a Taylor series in the initial Lagrangian dark matter density fluctuation field. We show that if this Lagrangian bias is local, and the initial conditions are Gaussian, then the two-point cross-correlation between halos and mass should be linearly proportional to the mass-mass auto-correlation function. This statement is exact and valid on all scales; there are no higher order contributions, e.g., from terms proportional to products or convolutions of two-point functions, which one might have thought would appear upon truncating the Taylor series of the halo bias function. In addition, the auto-correlation function of locally biased tracers can be written as a Taylor series in the auto-correlation function of the mass; there are no terms involving, e.g., derivatives or convolutions. Moreover, although the leading order coefficient, the linear bias factor of the auto-correlation function is just the square of that for the cross-correlation, it is the same as that obtained from expanding the mean number of halos as a function of the local density only in the large-scale limit. In principle, these relations allow simple tests of whether or not halo bias is indeed local in Lagrangian space. We discuss why things are more complicated in practice. We also discuss our results in light of recent work on the renormalizability of halo bias, demonstrating that it is better to renormalize than not. We use the Lognormal model to illustrate many of our findings
Germano, Fabrizio
2008-01-01
Within the spokes model of Chen and Riordan (2007) that allows for non-localized competition among arbitrary numbers of media outlets, we quantify the effect of concentration of ownership on quality and bias of media content. A main result shows that too few commercial outlets, or better, too few separate owners of commercial outlets can lead to substantial bias in equilibrium. Increasing the number of outlets (commercial and non-commercial) tends to bring down this bias; but the strong...
DEFF Research Database (Denmark)
Drecourt, J.-P.; Madsen, H.; Rosbjerg, Dan
2006-01-01
This paper reviews two different approaches that have been proposed to tackle the problems of model bias with the Kalman filter: the use of a colored noise model and the implementation of a separate bias filter. Both filters are implemented with and without feedback of the bias into the model state...... illustrated on a simple one-dimensional groundwater problem. The results show that the presented filters outperform the standard Kalman filter and that the implementations with bias feedback work in more general conditions than the implementations without feedback. 2005 Elsevier Ltd. All rights reserved....
... Data Consumer Opinion Surveys Home / Research & Statistics Injury Statistics This is the statistic reports page for scientific ... Home Appliances, Maintenance and Construction Injury Statistics Injury Statistics September 30, 2012 Submersions Related to Non-Pool ...
International Nuclear Information System (INIS)
This documents Phase 1 determinations on sampler induced bias for four sampler types used in tank characterization. Each sampler, grab sampler or bottle-on-a-string, auger sampler, sludge sampler and universal sampler, is briefly discussed and their physical limits noted. Phase 2 of this document will define additional testing and analysis to further define Sampler Bias
Gender bias in the force concept inventory?
Dietz, R. D.; Pearson, R. H.; Semak, M. R.; Willis, C. W.
2012-02-01
Could the well-established fact that males tend to score higher than females on the Force Concept Inventory (FCI) be due to gender bias in the questions? The eventual answer to the question hinges on the definition of bias. We assert that a question is biased only if a factor other than ability (in this case gender) affects the likelihood that a student will answer the question correctly. The statistical technique of differential item functioning allows us to control for ability in our analysis of student performance on each of the thirty FCI questions. This method uses the total score on the FCI as the measure of ability. We conclude that the evidence for gender bias in the FCI questions is marginal at best.
Galaxy Bias and Primordial Non-Gaussianity
Assassi, Valentin; Schmidt, Fabian
2015-01-01
We present a systematic study of galaxy biasing in the presence of primordial non-Gaussianity. For a large class of non-Gaussian initial conditions, we define a general bias expansion and prove that it is closed under renormalization, thereby showing that the basis of operators in the expansion is complete. We then study the effects of primordial non-Gaussianity on the statistics of galaxies. We show that the equivalence principle enforces a relation between the scale-dependent bias in the galaxy power spectrum and that in the dipolar part of the bispectrum. This provides a powerful consistency check to confirm the primordial origin of any observed scale-dependent bias. Finally, we also discuss the imprints of anisotropic non-Gaussianity as motivated by recent studies of higher-spin fields during inflation.
Galaxy bias and primordial non-Gaussianity
Assassi, Valentin; Baumann, Daniel; Schmidt, Fabian
2015-12-01
We present a systematic study of galaxy biasing in the presence of primordial non-Gaussianity. For a large class of non-Gaussian initial conditions, we define a general bias expansion and prove that it is closed under renormalization, thereby showing that the basis of operators in the expansion is complete. We then study the effects of primordial non-Gaussianity on the statistics of galaxies. We show that the equivalence principle enforces a relation between the scale-dependent bias in the galaxy power spectrum and that in the dipolar part of the bispectrum. This provides a powerful consistency check to confirm the primordial origin of any observed scale-dependent bias. Finally, we also discuss the imprints of anisotropic non-Gaussianity as motivated by recent studies of higher-spin fields during inflation.
Sociocognitive Biases in the Evaluation Process.
Perloff, Richard M.; And Others
1980-01-01
Causes of evaluator bias are: overemphasizing concrete, salient, and retrievable information; reporting only evidence which confirms hypothesis; focusing on stable personality factors, rather than on situation and environment; developing positive perceptions of a program as both an evaluator and a highly involved participant; statistical naivete;…
Systematic review of the empirical evidence of study publication bias and outcome reporting bias.
Directory of Open Access Journals (Sweden)
Kerry Dwan
Full Text Available BACKGROUND: The increased use of meta-analysis in systematic reviews of healthcare interventions has highlighted several types of bias that can arise during the completion of a randomised controlled trial. Study publication bias has been recognised as a potential threat to the validity of meta-analysis and can make the readily available evidence unreliable for decision making. Until recently, outcome reporting bias has received less attention. METHODOLOGY/PRINCIPAL FINDINGS: We review and summarise the evidence from a series of cohort studies that have assessed study publication bias and outcome reporting bias in randomised controlled trials. Sixteen studies were eligible of which only two followed the cohort all the way through from protocol approval to information regarding publication of outcomes. Eleven of the studies investigated study publication bias and five investigated outcome reporting bias. Three studies have found that statistically significant outcomes had a higher odds of being fully reported compared to non-significant outcomes (range of odds ratios: 2.2 to 4.7. In comparing trial publications to protocols, we found that 40-62% of studies had at least one primary outcome that was changed, introduced, or omitted. We decided not to undertake meta-analysis due to the differences between studies. CONCLUSIONS: Recent work provides direct empirical evidence for the existence of study publication bias and outcome reporting bias. There is strong evidence of an association between significant results and publication; studies that report positive or significant results are more likely to be published and outcomes that are statistically significant have higher odds of being fully reported. Publications have been found to be inconsistent with their protocols. Researchers need to be aware of the problems of both types of bias and efforts should be concentrated on improving the reporting of trials.
A generic algorithm for reducing bias in parametric estimation
Kosmidis, I.; Firth, D
2010-01-01
A general iterative algorithm is developed for the computation of reduced-bias parameter estimates in regular statistical models through adjustments to the score function. The algorithm unifies and provides appealing new interpretation for iterative methods that have been published previously for some specific model classes. The new algorithm can use fully be viewed as a series of iterative bias corrections, thus facilitating the adjusted score approach to bias reduction in any model for whic...
All your biases belong to us: Breaking RC4 in WPA-TKIP and TLS
Vanhoef, Mathy; Piessens, Frank
2015-01-01
We present new biases in RC4, break the Wi-Fi Protected Access Temporal Key Integrity Protocol (WPA-TKIP), and design a practical plaintext recovery attack against the Transport Layer Security (TLS) protocol. To empirically find new biases in the RC4 keystream we use statistical hypothesis tests. This reveals many new biases in the initial keystream bytes, as well as several new longterm biases. Our fixed-plaintext recovery algorithms are capable of using multiple types of biases, and return ...
Why is "S" a Biased Estimate of [sigma]?
Sanqui, Jose Almer T.; Arnholt, Alan T.
2011-01-01
This article describes a simulation activity that can be used to help students see that the estimator "S" is a biased estimator of [sigma]. The activity can be implemented using either a statistical package such as R, Minitab, or a Web applet. In the activity, the students investigate and compare the bias of "S" when sampling from different…
Harassment, Bias, and Discrimination.
Welliver, Paul W.
1995-01-01
Discusses a new principle which has been added to the AECT (Association for Educational Communications and Technology) Code of Professional Ethics regarding discrimination, harassment, and bias. An example is presented which illustrates a violation of a professional colleague's rights. (LRW)
DEFF Research Database (Denmark)
Paldam, Martin
censoring: selection by the size of estimate; SR3 selects the optimal combination of fit and size; and SR4 selects the first satisficing result. The last four SRs are steered by priors and result in bias. The MST and the FAT-PET have been developed for detection and correction of such bias. The simulations...... are made by data variation, while the model is the same. It appears that SR0 generates narrow funnels much at odds with observed funnels, while the other four funnels look more realistic. SR1 to SR4 give the mean a substantial bias that confirms the prior causing the bias. The FAT-PET MRA works well...
Introduction to Unconscious Bias
Schmelz, Joan T.
2010-05-01
We all have biases, and we are (for the most part) unaware of them. In general, men and women BOTH unconsciously devalue the contributions of women. This can have a detrimental effect on grant proposals, job applications, and performance reviews. Sociology is way ahead of astronomy in these studies. When evaluating identical application packages, male and female University psychology professors preferred 2:1 to hire "Brian” over "Karen” as an assistant professor. When evaluating a more experienced record (at the point of promotion to tenure), reservations were expressed four times more often when the name was female. This unconscious bias has a repeated negative effect on Karen's career. This talk will introduce the concept of unconscious bias and also give recommendations on how to address it using an example for a faculty search committee. The process of eliminating unconscious bias begins with awareness, then moves to policy and practice, and ends with accountability.
Mishra, Anil V; Umaru B. Conteh
2014-01-01
This paper constructs the float adjusted measure of home bias and explores the determinants of bond home bias by employing the International Monetary Fund's high quality dataset (2001 to 2009) on cross-border bond investment. The paper finds that Australian investors' prefer investing in countries with higher economic development and more developed bond markets. Exchange rate volatility appears to be an impediment for cross-border bond investment. Investors prefer investing in countries with ...
Measuring agricultural policy bias
DEFF Research Database (Denmark)
Jensen, Henning Tarp; Robinson, Sherman; Tarp, Finn
2010-01-01
that the agricultural price incentive bias generally perceived to exist during the 1980s was largely eliminated during the 1990s. Results also demonstrate that general equilibrium effects and country-specific characteristics are crucial for determining the sign and magnitude of agricultural bias. Our comprehensive...... protection measure is therefore uniquely suited to capture the full impact of trade policies on relative agricultural price incentives....
Goodfriend, Marvin
1991-01-01
Aggregation in the presence of data-processing lags distorts the information content of data, violating orthogonality restrictions that hold at the individual level. Though the phenomenon is general, it is illustrated here for the life-cycle-permanent-income model. Cross-section and pooled-panel data induce information-aggregation bias akin to that in aggregate time series. Calculations show that information aggregation can seriously bias tests of the life-cycle model on aggregate time series...
Biased causal inseparable game
Bhattacharya, Some Sankar
2015-01-01
Here we study the \\emph{causal inseparable} game introduced in [\\href{http://www.nature.com/ncomms/journal/v3/n10/full/ncomms2076.html}{Nat. Commun. {\\bf3}, 1092 (2012)}], but it's biased version. Two separated parties, Alice and Bob, generate biased bits (say input bit) in their respective local laboratories. Bob generates another biased bit (say decision bit) which determines their goal: whether Alice has to guess Bob's bit or vice-verse. Under the assumption that events are ordered with respect to some global causal relation, we show that the success probability of this biased causal game is upper bounded, giving rise to \\emph{biased causal inequality} (BCI). In the \\emph{process matrix} formalism, which is locally in agreement with quantum physics but assume no global causal order, we show that there exist \\emph{inseparable} process matrices that violate the BCI for arbitrary bias in the decision bit. In such scenario we also derive the maximal violation of the BCI under local operations involving tracele...
Janet Gale Stotsky
1996-01-01
This paper examines the nature of gender bias in tax systems. Gender bias takes both explicit and implicit forms. Explicit gender bias is found in many personal income tax systems. Several countries, especially those in Western Europe, have undertaken to eliminate explicit gender bias in recent years. It is more difficult to identify implicit gender bias, since this depends in large part on value judgments as to desirable social and economic behavior. Implicit gender bias has also been a targ...
Discrete angle biasing in Monte Carlo radiation transport
International Nuclear Information System (INIS)
An angular biasing procedure is presented for use in Monte Carlo radiation transport with discretized scattering angle data. As in more general studies, the method is shown to reduce statistical weight fluctuations when it is combined with the exponential transformation. This discrete data application has a simple analytic form which is problem independent. The results from a sample problem illustrate the variance reduction and efficiency characteristics of the combined biasing procedures, and a large neutron and gamma ray integral experiment is also calculated. A proposal is given for the possible code generation of the biasing parameter p and the preferential direction /ovr/Omega//0 used in the combined biasing schemes
... What Is Cancer? Cancer Statistics Cancer Disparities Cancer Statistics Cancer has a major impact on society in ... success of efforts to control and manage cancer. Statistics at a Glance: The Burden of Cancer in ...
Non-Gaussian bias: insights from discrete density peaks
International Nuclear Information System (INIS)
Corrections induced by primordial non-Gaussianity to the linear halo bias can be computed from a peak-background split or the widespread local bias model. However, numerical simulations clearly support the prediction of the former, in which the non-Gaussian amplitude is proportional to the linear halo bias. To understand better the reasons behind the failure of standard Lagrangian local bias, in which the halo overdensity is a function of the local mass overdensity only, we explore the effect of a primordial bispectrum on the 2-point correlation of discrete density peaks. We show that the effective local bias expansion to peak clustering vastly simplifies the calculation. We generalize this approach to excursion set peaks and demonstrate that the resulting non-Gaussian amplitude, which is a weighted sum of quadratic bias factors, precisely agrees with the peak-background split expectation, which is a logarithmic derivative of the halo mass function with respect to the normalisation amplitude. We point out that statistics of thresholded regions can be computed using the same formalism. Our results suggest that halo clustering statistics can be modelled consistently (in the sense that the Gaussian and non-Gaussian bias factors agree with peak-background split expectations) from a Lagrangian bias relation only if the latter is specified as a set of constraints imposed on the linear density field. This is clearly not the case of standard Lagrangian local bias. Therefore, one is led to consider additional variables beyond the local mass overdensity
DEFF Research Database (Denmark)
Jensen, Henning Tarp; Robinson, Sherman; Tarp, Finn
The measurement issue is the key issue in the literature on trade policy-induced agri-cultural price incentive bias. This paper introduces a general equilibrium effective rate of protection (GE-ERP) measure, which extends and generalizes earlier partial equilibrium nominal protection measures....... For the 15 sample countries, the results indicate that the agricultural price incentive bias, which was generally perceived to exist during the 1980s, was largely eliminated during the 1990s. The results also demonstrate that general equilibrium effects and country-specific characteristics - including trade...... shares and intersectoral linkages - are crucial for determining the sign and magnitude of trade policy bias. The GE-ERP measure is therefore uniquely suited to capture the full impact of trade policies on agricultural price incentives. A Monte Carlo procedure confirms that the results are robust...
Statistical Control of Measurement Quality
International Nuclear Information System (INIS)
Effective nuclear materials management, and hence design and operation of associated material control systems, depend heavily on the quality of the quantitative data on which they are based. Information concerning the reliability of the measurement methods employed is essential to both the determination of data requirements and the evaluation of results obtained. Any method of analysis should be (1) relatively free from bias and (2) reproducible, or, in more usual terminology, precise. Many statistical techniques are available to evaluate and control the reproducibility of analytical results. Economical and effective experimental designs have been developed for the segregation of different sources of measurement error. Procedures have been developed or adapted tot use in maintaining and controlling the precision of routine measurements. All of these techniques require that at least some measurements must be duplicated, but duplication of all measurements can be justified only when the detection of every gross error, or mistake, is extremely important. Three types of measurement bias can be considered: (1) bias relative to a standard, (2) bias relative to prior experience, and (3) bias relative to a group. The first refers to the degree to which the measurements obtained deviate systematically from some ''standard'' which is unbiased either (1) by definition, or (2) because all known sources of bias have been removed. The second in concerned with the presence of systematic differences over a period of time. The third type of bias concerns the relationship between different physical entities or individuals at a given time. Recent developments in statistical methodology applicable to the evaluation of all three types of bias are discussed. Examples of the use of the statistical techniques discussed on Hanford data are presented. (author)
Development of a Test of Cognitive Bias in Medical Decision Making.
Hershberger, Paul J.; And Others
1994-01-01
Poor performance of medical students, residents, and faculty on a newly developed Inventory of Cognitive Biases in Medicine, suggests that cognitive biases detract from reliance on logical and statistical strategies in medical decision making. The test shows promise for use in instructional and research efforts to reduce such bias. (Author/MSE)
Using biased discriminant analysis for email filtering
Gomez, Juan Carlos; Moens, Marie-Francine
2010-01-01
This paper reports on email filtering based on content features. We test the validity of a novel statistical feature extraction method, which relies on dimensionality reduction to retain the most informative and discriminative features from messages. The approach, named Biased Discriminant Analysis (BDA), aims at finding a feature space transformation that closely clusters positive examples while pushing away the negative ones. This method is an extension of Linear Discriminant Analysis (L...
Addor, Nans; Rohrer, Marco; Furrer, Reinhard; Seibert, Jan
2016-03-01
Bias adjustment methods usually do not account for the origins of biases in climate models and instead perform empirical adjustments. Biases in the synoptic circulation are for instance often overlooked when postprocessing regional climate model (RCM) simulations driven by general circulation models (GCMs). Yet considering atmospheric circulation helps to establish links between the synoptic and the regional scale, and thereby provides insights into the physical processes leading to RCM biases. Here we investigate how synoptic circulation biases impact regional climate simulations and influence our ability to mitigate biases in precipitation and temperature using quantile mapping. We considered 20 GCM-RCM combinations from the ENSEMBLES project and characterized the dominant atmospheric flow over the Alpine domain using circulation types. We report in particular a systematic overestimation of the frequency of westerly flow in winter. We show that it contributes to the generalized overestimation of winter precipitation over Switzerland, and this wet regional bias can be reduced by improving the simulation of synoptic circulation. We also demonstrate that statistical bias adjustment relying on quantile mapping is sensitive to circulation biases, which leads to residual errors in the postprocessed time series. Overall, decomposing GCM-RCM time series using circulation types reveals connections missed by analyses relying on monthly or seasonal values. Our results underscore the necessity to better diagnose process misrepresentation in climate models to progress with bias adjustment and impact modeling.
Forster, Malcolm R
2011-01-01
Statisticians and philosophers of science have many common interests but restricted communication with each other. This volume aims to remedy these shortcomings. It provides state-of-the-art research in the area of philosophy of statistics by encouraging numerous experts to communicate with one another without feeling "restricted” by their disciplines or thinking "piecemeal” in their treatment of issues. A second goal of this book is to present work in the field without bias toward any particular statistical paradigm. Broadly speaking, the essays in this Handbook are concerned with problems of induction, statistics and probability. For centuries, foundational problems like induction have been among philosophers' favorite topics; recently, however, non-philosophers have increasingly taken a keen interest in these issues. This volume accordingly contains papers by both philosophers and non-philosophers, including scholars from nine academic disciplines.
Statistical models for seismic magnitude
Christoffersson, Anders
1980-02-01
In this paper some statistical models in connection with seismic magnitude are presented. Two main situations are treated. The first deals with the estimation of magnitude for an event, using a fixed network of stations and taking into account the detection and bias properties of the individual stations. The second treats the problem of estimating seismicity, and detection and bias properties of individual stations. The models are applied to analyze the magnitude bias effects for an earthquake aftershock sequence from Japan, as recorded by a hypothetical network of 15 stations. It is found that network magnitudes computed by the conventional averaging technique are considerably biased, and that a maximum likelihood approach using instantaneous noise-level estimates for non-detecting stations gives the most consistent magnitude estimates. Finally, the models are applied to evaluate the detection characteristics and associated seismicity as recorded by three VELA arrays: UBO (Uinta Basin), TFO (Tonto Forest) and WMO (Wichita Mountains).
Dujmovic, Vida; Morin, Pat
2008-01-01
A data structure, called a biased range tree, is presented that preprocesses a set S of n points in R^2 and a query distribution D for 2-sided orthogonal range counting queries. The expected query time for this data structure, when queries are drawn according to D, matches, to within a constant factor, that of the optimal decision tree for S and D. The memory and preprocessing requirements of the data structure are O(n log n).
Kadelbach, Irmgard
2003-01-01
Die Elektrocochleographie (EcoG) ist eine der vielversprechendsten Methoden, cochleäre Dysfunktionen mit objektiver Diagnostik zu verifizieren. Erweitert durch das Prinzip des Biasings, also der gleichzeitigen Präsentation von Testtönen in einen niederfrequenten 52-Hz-Sinusdauerton, läßt sich die Funktion der Cochlea und eine möglicherweise pathologische Arbeitsweise aufdecken. In der Auswertung der Amplituden des Summationspotentials (SP), des cochleären Mikrophonpotentials (CM) und des Summ...
Photoconductivity of biased graphene
Freitag, Marcus; Low, Tony; Xia, Fengnian; Avouris, Phaedon
2012-01-01
Graphene is a promising candidate for optoelectronic applications such as photodetectors, terahertz imagers, and plasmonic devices. The origin of photoresponse in graphene junctions has been studied extensively and is attributed to either thermoelectric or photovoltaic effects. In addition, hot carrier transport and carrier multiplication are thought to play an important role. Here we report the intrinsic photoresponse in biased but otherwise homogeneous graphene. In this classic photoconduct...
Draper, D.
2001-01-01
© 2012 Springer Science+Business Media, LLC. All rights reserved. Article Outline: Glossary Definition of the Subject and Introduction The Bayesian Statistical Paradigm Three Examples Comparison with the Frequentist Statistical Paradigm Future Directions Bibliography
... www.nlm.nih.gov/medlineplus/usestatistics.html MedlinePlus Statistics To use the sharing features on this page, ... By Quarter View image full size Quarterly User Statistics Quarter Page Views Unique Visitors Oct-Dec-98 ...
International Nuclear Information System (INIS)
A method for detecting and identifying biases in the pressure and level sensors of a pressurized water reactor (PWR) pressurizer is described. The generalized likelihood ratio (GLR) technique performs statistical tests on the innovations sequence of a Kalman filter state estimator and is capable of determining when a bias appears, in what sensor the bias exists, and estimating the bias magnitude. Simulation results using a second-order linear, discrete PWR pressurizer model demonstrate the capabilities of the GLR method
Assessing Bias in Search Engines.
Mowshowitz, Abbe; Kawaguchi, Akira
2002-01-01
Addresses the measurement of bias in search engines on the Web, defining bias as the balance and representation of items in a collection retrieved from a database for a set of queries. Assesses bias by measuring the deviation from the ideal of the distribution produced by a particular search engine. (Author/LRW)
Casella, George
2002-01-01
"Statistical Inference is a delightfully modern text on statistical theory and deserves serious consideration from every teacher of a graduate- or advanced undergraduate-level first course in statistical theory. . . Chapters 1-5 provide plenty of interesting examples illustrating either the basic concepts of probability or the basic techniques of finding distribution. . . The book has unique features [throughout Chapters 6-12] for example, I have never seen in any comparable text such extensive discussion of ancillary statistics [Ch. 6], including Basu's theorem, dealing with the independence of complete sufficient statistics and ancillary statistics. Basu's theorem is such a useful tool that it should be available to every graduate student of statistics. . . The derivation of the analysis of variance (ANOVA)F test in Chapter 11 via the union-intersection principle is very nice. . . Chapter 12 contains, in addition to the standard regression model, errors-in-variables models. This topic will be of considerabl...
Test Bias and the Elimination of Racism
Sedlacek, William E.
1977-01-01
Three types of test bias are discussed: content bias, atmosphere bias, and use bias. Use bias is considered the most important. Tests reflect the bias in society, and eliminating test bias means eliminating racism and sexism in society. A six-stage model to eliminate racism and sexism is presented. (Author)
Quantifying the Biases of Spectroscopically Selected Gravitational Lenses
Arneson, Ryan A; Bolton, Adam S
2012-01-01
Spectroscopic selection has been the most productive technique for the selection of galaxy-scale strong gravitational lens systems with known redshifts. Statistically significant samples of strong lenses provide a powerful method for measuring the mass-density parameters of the lensing population, but results can only be generalized to the parent population if the lensing selection biases are sufficiently understood. We perform controlled Monte Carlo simulations of spectroscopic lens surveys in order to quantify the bias of lenses relative to parent galaxies in velocity dispersion, mass axis ratio, and mass density profile. For parameters typical of the SLACS and BELLS surveys, we find: (1) no significant mass axis ratio detection bias of lenses relative to parent galaxies; (2) a very small detection bias toward shallow mass density profiles, which is likely negligible compared to other sources of uncertainty in this parameter; (3) a detection bias towards smaller Einstein radius for systems drawn from parent...
The Twelfth Man? Refereeing Bias in English and German Soccer
Babatunde Buraimo; David Forrest; Robert Simmons
2007-01-01
This paper investigates potential bias in awards of player disciplinary sanctions, in the form of cautions (yellow cards) and dismissals (red cards) by referees in the English Premier League and the Bundesliga. Previous studies of behaviour of soccer referees have not adequately incorporated within-game information. Descriptive statistics from our samples clearly show that home teams receive fewer yellow and red cards than away teams. But biases may be wrongly identified where the modeller ha...
A new method to measure galaxy bias
Pollack, Jennifer E; Porciani, Cristiano
2013-01-01
We present a new approach for modelling halo bias that utilizes the full non-linear information contained in the moments of the matter density field. The basis of our technique is to derive this information directly from a set of numerical simulations. Although our method is general, we perform a case study based on the local Eulerian bias scheme truncated to second-order. Using 200 N-body simulations that cover a total comoving volume of 675 (Gpc/h)^3, we measure several 2- and 3-point statistics of the halo distribution to unprecedented accuracy. We then use the bias model to fit the halo-halo power spectrum, the halo-matter cross spectrum and the corresponding three bispectra for wavenumbers in the range 0.04 < k < 0.12 h Mpc^-1. While all fits accurately describe the data, we find that the constraints on the bias parameters obtained using the full non-linear information differ significantly from those derived using leading-order standard perturbation theory. Hence, neglecting the full non-linear inf...
Bias and Causation Models and Judgment for Valid Comparisons
Weisberg, Herbert I
2010-01-01
A one-of-a-kind resource on identifying and dealing with bias in statistical research on causal effects. Do cell phones cause cancer? Can a new curriculum increase student achievement? Determining what the real causes of such problems are, and how powerful their effects may be, are central issues in research across various fields of study. Some researchers are highly skeptical of drawing causal conclusions except in tightly controlled randomized experiments, while others discount the threats posed by different sources of bias, even in less rigorous observational studies. Bias and Causation pre
The Bias of the Gini Coefficient due to Grouping
VAN OURTI, Tom; Clarke, Philip
2008-01-01
Read also the publication in the 'Review of Economics and Statistics' , 2010, 93(3), 982-994. We propose a first order bias correction term for the Gini index to reduce the bias due to grouping. The first order correction term is obtained from studying the estimator of the Gini index within a measurement error framework. In addition, it reveals an intuitive formula for the remaining second order bias which is useful in empirical analyses. We analyze the empirical performance of our first orde...
Presence of bias in radiographer plain film reading performance studies
International Nuclear Information System (INIS)
Purpose To raise awareness of the frequency of bias that can affect the quality of radiographer plain film reading performance studies. Methods Studies that assessed radiographer(s) plain film reading performance were located by searching electronic databases and grey literature, hand-searching journals, personal communication and scanning reference lists. Thirty studies were judged eligible from all data sources. Results A one-way analysis of variance (ANOVA) demonstrates no statistically significant difference (P=0.25) in the mean proportion of biases present from diagnostic accuracy (0.37), performance (0.42) and outcome (0.44) study designs. Pearson's correlation coefficient showed no statistically significant linear association between the proportion of biases present for the three different study designs and the year that the study was performed. The frequency of biases in film and observer selection and application of the reference standard was quite low. In contrast, many biases were present concerning independence of film reporting and comparison of reports for concordance. Conclusions The findings indicate variation in the presence of bias in radiographer plain film reading performance studies. The careful consideration of bias is an essential component of study quality and hence the validity of the evidence-base used to underpin radiographic reporting policy
Publication Bias ( The "File-Drawer Problem") in Scientific Inference
Scargle, Jeffrey D.; DeVincenzi, Donald (Technical Monitor)
1999-01-01
Publication bias arises whenever the probability that a study is published depends on the statistical significance of its results. This bias, often called the file-drawer effect since the unpublished results are imagined to be tucked away in researchers' file cabinets, is potentially a severe impediment to combining the statistical results of studies collected from the literature. With almost any reasonable quantitative model for publication bias, only a small number of studies lost in the file-drawer will produce a significant bias. This result contradicts the well known Fail Safe File Drawer (FSFD) method for setting limits on the potential harm of publication bias, widely used in social, medical and psychic research. This method incorrectly treats the file drawer as unbiased, and almost always miss-estimates the seriousness of publication bias. A large body of not only psychic research, but medical and social science studies, has mistakenly relied on this method to validate claimed discoveries. Statistical combination can be trusted only if it is known with certainty that all studies that have been carried out are included. Such certainty is virtually impossible to achieve in literature surveys.
Szulc, Stefan
1965-01-01
Statistical Methods provides a discussion of the principles of the organization and technique of research, with emphasis on its application to the problems in social statistics. This book discusses branch statistics, which aims to develop practical ways of collecting and processing numerical data and to adapt general statistical methods to the objectives in a given field.Organized into five parts encompassing 22 chapters, this book begins with an overview of how to organize the collection of such information on individual units, primarily as accomplished by government agencies. This text then
Goodman, Joseph W
2015-01-01
This book discusses statistical methods that are useful for treating problems in modern optics, and the application of these methods to solving a variety of such problems This book covers a variety of statistical problems in optics, including both theory and applications. The text covers the necessary background in statistics, statistical properties of light waves of various types, the theory of partial coherence and its applications, imaging with partially coherent light, atmospheric degradations of images, and noise limitations in the detection of light. New topics have been introduced i
Directory of Open Access Journals (Sweden)
Kerry Dwan
Full Text Available BACKGROUND: The increased use of meta-analysis in systematic reviews of healthcare interventions has highlighted several types of bias that can arise during the completion of a randomised controlled trial. Study publication bias and outcome reporting bias have been recognised as a potential threat to the validity of meta-analysis and can make the readily available evidence unreliable for decision making. METHODOLOGY/PRINCIPAL FINDINGS: In this update, we review and summarise the evidence from cohort studies that have assessed study publication bias or outcome reporting bias in randomised controlled trials. Twenty studies were eligible of which four were newly identified in this update. Only two followed the cohort all the way through from protocol approval to information regarding publication of outcomes. Fifteen of the studies investigated study publication bias and five investigated outcome reporting bias. Three studies have found that statistically significant outcomes had a higher odds of being fully reported compared to non-significant outcomes (range of odds ratios: 2.2 to 4.7. In comparing trial publications to protocols, we found that 40-62% of studies had at least one primary outcome that was changed, introduced, or omitted. We decided not to undertake meta-analysis due to the differences between studies. CONCLUSIONS: This update does not change the conclusions of the review in which 16 studies were included. Direct empirical evidence for the existence of study publication bias and outcome reporting bias is shown. There is strong evidence of an association between significant results and publication; studies that report positive or significant results are more likely to be published and outcomes that are statistically significant have higher odds of being fully reported. Publications have been found to be inconsistent with their protocols. Researchers need to be aware of the problems of both types of bias and efforts should be
Statistical theory and inference
Olive, David J
2014-01-01
This text is for a one semester graduate course in statistical theory and covers minimal and complete sufficient statistics, maximum likelihood estimators, method of moments, bias and mean square error, uniform minimum variance estimators and the Cramer-Rao lower bound, an introduction to large sample theory, likelihood ratio tests and uniformly most powerful tests and the Neyman Pearson Lemma. A major goal of this text is to make these topics much more accessible to students by using the theory of exponential families. Exponential families, indicator functions and the support of the distribution are used throughout the text to simplify the theory. More than 50 ``brand name" distributions are used to illustrate the theory with many examples of exponential families, maximum likelihood estimators and uniformly minimum variance unbiased estimators. There are many homework problems with over 30 pages of solutions.
Is there gender bias in nursing research?
Polit, Denise F; Beck, Cheryl Tatano
2008-10-01
Using data from a consecutive sample of 259 studies published in four leading nursing research journals in 2005-2006, we examined whether nurse researchers favor females as study participants. On average, 75.3% of study participants were female, and 38% of studies had all-female samples. The bias favoring female participants was statistically significant and persistent. The bias was observed regardless of funding source, methodological features, and other participant and researcher characteristics, with one exception: studies that had male investigators had more sex-balanced samples. When designing studies, nurse researchers need to pay close attention to who will benefit from their research and to whether they are leaving out a specific group about which there is a gap in knowledge. PMID:18324681
Spatial Bias in Field-Estimated Unsaturated Hydraulic Properties
Energy Technology Data Exchange (ETDEWEB)
HOLT,ROBERT M.; WILSON,JOHN L.; GLASS JR.,ROBERT J.
2000-12-21
Hydraulic property measurements often rely on non-linear inversion models whose errors vary between samples. In non-linear physical measurement systems, bias can be directly quantified and removed using calibration standards. In hydrologic systems, field calibration is often infeasible and bias must be quantified indirectly. We use a Monte Carlo error analysis to indirectly quantify spatial bias in the saturated hydraulic conductivity, K{sub s}, and the exponential relative permeability parameter, {alpha}, estimated using a tension infiltrometer. Two types of observation error are considered, along with one inversion-model error resulting from poor contact between the instrument and the medium. Estimates of spatial statistics, including the mean, variance, and variogram-model parameters, show significant bias across a parameter space representative of poorly- to well-sorted silty sand to very coarse sand. When only observation errors are present, spatial statistics for both parameters are best estimated in materials with high hydraulic conductivity, like very coarse sand. When simple contact errors are included, the nature of the bias changes dramatically. Spatial statistics are poorly estimated, even in highly conductive materials. Conditions that permit accurate estimation of the statistics for one of the parameters prevent accurate estimation for the other; accurate regions for the two parameters do not overlap in parameter space. False cross-correlation between estimated parameters is created because estimates of K{sub s} also depend on estimates of {alpha} and both parameters are estimated from the same data.
Glaz, Joseph
2009-01-01
Suitable for graduate students and researchers in applied probability and statistics, as well as for scientists in biology, computer science, pharmaceutical science and medicine, this title brings together a collection of chapters illustrating the depth and diversity of theory, methods and applications in the area of scan statistics.
International Nuclear Information System (INIS)
Research on the exchange bias (EB) phenomenon has witnessed a flurry of activity during recent years, which stems from its use in magnetic sensors and as stabilizers in magnetic reading heads. EB was discovered in 1956 but it attracted only limited attention until these applications, closely related to giant magnetoresistance, were developed during the last decade. In this review, I initially give a short introduction, listing the most salient experimental results and what is required from an EB theory. Next, I indicate some of the obstacles in the road towards a satisfactory understanding of the phenomenon. The main body of the text reviews and critically discusses the activity that has flourished, mainly during the last 5 years, in the theoretical front. Finally, an evaluation of the progress made, and a critical assessment as to where we stand nowadays along the road to a satisfactory theory, is presented
Measuring nonlocal Lagrangian peak bias
Biagetti, Matteo; Desjacques, Vincent; Paranjape, Aseem
2013-01-01
In the Lagrangian approach to halo clustering, nonlocal bias can be generated either in the initial conditions or by the subsequent gravitational motions. Here, we investigate nonlocal Lagrangian bias contributions involving gradients of the linear density field, for which we have predictions from the excursion set peak formalism. We reformulate this approach in order to explicitly take into account the variable describing the crossing of the collapse barrier. This enables us to write down a bias expansion which includes all the bias terms, including the nonlocal ones. Having checked that the model furnishes a reasonable fit to the halo mass function, we extend the 1-point cross-correlation technique of Musso, Paranjape & Sheth (2012) to bias contributions that are chi-squared distributed. We validate the method with numerical realizations of peaks of Gaussian random fields before applying it to N-body simulations. We focus on the lowest (quadratic) order nonlocal bias factors predicted by the excursion s...
Ross, Sheldon M
2010-01-01
In this 3rd edition revised text, master expositor Sheldon Ross has produced a unique work in introductory statistics. The text's main merits are the clarity of presentation, contemporary examples and applications from diverse areas, and an explanation of intuition and ideas behind the statistical methods. Concepts are motivated, illustrated and explained in a way that attempts to increase one's intuition. To quote from the preface, ""It is only when a student develops a feel or intuition for statistics that she or he is really on the path toward making sense of data."" Ross achieves this
Ross, Sheldon M
2005-01-01
In this revised text, master expositor Sheldon Ross has produced a unique work in introductory statistics. The text's main merits are the clarity of presentation, contemporary examples and applications from diverse areas, and an explanation of intuition and ideas behind the statistical methods. To quote from the preface, ""It is only when a student develops a feel or intuition for statistics that she or he is really on the path toward making sense of data."" Ross achieves this goal through a coherent mix of mathematical analysis, intuitive discussions and examples.* Ross's clear writin
Feiveson, Alan H.; Foy, Millennia; Ploutz-Snyder, Robert; Fiedler, James
2014-01-01
Do you have elevated p-values? Is the data analysis process getting you down? Do you experience anxiety when you need to respond to criticism of statistical methods in your manuscript? You may be suffering from Insufficient Statistical Support Syndrome (ISSS). For symptomatic relief of ISSS, come for a free consultation with JSC biostatisticians at our help desk during the poster sessions at the HRP Investigators Workshop. Get answers to common questions about sample size, missing data, multiple testing, when to trust the results of your analyses and more. Side effects may include sudden loss of statistics anxiety, improved interpretation of your data, and increased confidence in your results.
Wannier, Gregory H
2010-01-01
Until recently, the field of statistical physics was traditionally taught as three separate subjects: thermodynamics, statistical mechanics, and kinetic theory. This text, a forerunner in its field and now a classic, was the first to recognize the outdated reasons for their separation and to combine the essentials of the three subjects into one unified presentation of thermal physics. It has been widely adopted in graduate and advanced undergraduate courses, and is recommended throughout the field as an indispensable aid to the independent study and research of statistical physics.Designed for
DEFF Research Database (Denmark)
Tryggestad, Kjell
2004-01-01
The study aims is to describe how the inclusion and exclusion of materials and calculative devices construct the boundaries and distinctions between statistical facts and artifacts in economics. My methodological approach is inspired by John Graunt's (1667) Political arithmetic and more recent work...... within constructivism and the field of Science and Technology Studies (STS). The result of this approach is here termed reversible statistics, reconstructing the findings of a statistical study within economics in three different ways. It is argued that all three accounts are quite normal, albeit in...... different ways. The presence and absence of diverse materials, both natural and political, is what distinguishes them from each other. Arguments are presented for a more symmetric relation between the scientific statistical text and the reader. I will argue that a more symmetric relation can be achieved by...
Serdobolskii, Vadim Ivanovich
2007-01-01
This monograph presents mathematical theory of statistical models described by the essentially large number of unknown parameters, comparable with sample size but can also be much larger. In this meaning, the proposed theory can be called "essentially multiparametric". It is developed on the basis of the Kolmogorov asymptotic approach in which sample size increases along with the number of unknown parameters.This theory opens a way for solution of central problems of multivariate statistics, which up until now have not been solved. Traditional statistical methods based on the idea of an infinite sampling often break down in the solution of real problems, and, dependent on data, can be inefficient, unstable and even not applicable. In this situation, practical statisticians are forced to use various heuristic methods in the hope the will find a satisfactory solution.Mathematical theory developed in this book presents a regular technique for implementing new, more efficient versions of statistical procedures. ...
The Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute works to provide information on cancer statistics in an effort to reduce the burden of cancer among the U.S. population.
U.S. Department of Health & Human Services — The CMS Center for Strategic Planning produces an annual CMS Statistics reference booklet that provides a quick reference for summary information about health...
Department of Homeland Security — Accident statistics available on the Coast Guard’s website by state, year, and one variable to obtain tables and/or graphs. Data from reports has been loaded for...
Adler, Robert; Ewing, John; Taylor, Peter
2009-01-01
This is a report about the use and misuse of citation data in the assessment of scientific research. The idea that research assessment must be done using ``simple and objective'' methods is increasingly prevalent today. The ``simple and objective'' methods are broadly interpreted as bibliometrics, that is, citation data and the statistics derived from them. There is a belief that citation statistics are inherently more accurate because they substitute simple numbers for complex judgments, and...
Baaquie, Belal E.
2012-01-01
A statistical generalization is made of microeconomics in the spirit of going from classical to statistical mechanics. The price and quantity of every commodity1 traded in the market, at each instant of time, is considered to be an independent random variable: all prices and quantities are considered to be stochastic processes, with the observed market prices being a random sample of the stochastic prices. The dynamics of market prices is determined by an action functional and, for concretene...
Error covariance calculation for forecast bias estimation in hydrologic data assimilation
Pauwels, Valentijn R. N.; De Lannoy, Gabriëlle J. M.
2015-12-01
To date, an outstanding issue in hydrologic data assimilation is a proper way of dealing with forecast bias. A frequently used method to bypass this problem is to rescale the observations to the model climatology. While this approach improves the variability in the modeled soil wetness and discharge, it is not designed to correct the results for any bias. Alternatively, attempts have been made towards incorporating dynamic bias estimates into the assimilation algorithm. Persistent bias models are most often used to propagate the bias estimate, where the a priori forecast bias error covariance is calculated as a constant fraction of the unbiased a priori state error covariance. The latter approach is a simplification to the explicit propagation of the bias error covariance. The objective of this paper is to examine to which extent the choice for the propagation of the bias estimate and its error covariance influence the filter performance. An Observation System Simulation Experiment (OSSE) has been performed, in which ground water storage observations are assimilated into a biased conceptual hydrologic model. The magnitudes of the forecast bias and state error covariances are calibrated by optimizing the innovation statistics of groundwater storage. The obtained bias propagation models are found to be identical to persistent bias models. After calibration, both approaches for the estimation of the forecast bias error covariance lead to similar results, with a realistic attribution of error variances to the bias and state estimate, and significant reductions of the bias in both the estimates of groundwater storage and discharge. Overall, the results in this paper justify the use of the traditional approach for online bias estimation with a persistent bias model and a simplified forecast bias error covariance estimation.
Bias in clinical intervention research
DEFF Research Database (Denmark)
Gluud, Lise Lotte
2006-01-01
Research on bias in clinical trials may help identify some of the reasons why investigators sometimes reach the wrong conclusions about intervention effects. Several quality components for the assessment of bias control have been suggested, but although they seem intrinsically valid, empirical...
Primordial black holes as biased tracers
Tada, Yuichiro
2015-01-01
Primordial black holes (PBHs) are theoretical black holes which may be formed during the radiation dominant era and, basically, caused by the gravitational collapse of radiational overdensities. It has been well known that in the context of the structure formation in our Universe such collapsed objects, e.g., halos/galaxies, could be considered as bias tracers of underlying matter fluctuations and the halo/galaxy bias has been studied well. Employing a peak-background split picture which is known to be a useful tool to discuss the halo bias, we consider the large scale clustering behavior of the PBH and propose an almost mass-independent constraint to the scenario that dark matters (DMs) consist of PBHs. We consider the case where the statistics of the primordial curvature perturbations is almost Gaussian, but with small local-type non-Gaussianity. If PBHs account for the DM abundance, such a large scale clustering of PBHs behaves as nothing but the matter isocurvature perturbation and constrained strictly by...
Anandamide mediates cognitive judgement bias in rats.
Kregiel, J; Malek, N; Popik, P; Starowicz, K; Rygula, R
2016-02-01
In the present study, we investigated the effects of acute pharmacological manipulation of the endocannabinoid (EC) system on the valence of cognitive judgement bias of rats in the ambiguous-cue interpretation (ACI) paradigm. To accomplish this goal, after initial behavioural training, different groups of rats received single, systemic injections of the irreversible anandamide (AEA) hydrolysis inhibitor URB597, the cannabinoid receptor type 1 (CB1) inverse agonist AM251, the cannabinoid receptor type 2 (CB2) inverse agonist AM630, the combination of URB597 and AM251, and a combination of URB597 and AM630 and were subsequently tested with the ACI paradigm. We report that URB597 at a dose of 1 mg/kg significantly biased animals towards positive interpretation of the ambiguous cue and that this effect was abolished by pre-treatment with AM251 (1 mg/kg) or AM630 (1 mg/kg). The CB1 and CB2 inverse agonists administered alone (1 mg/kg) had no statistically significant effects on the interpretation of the ambiguous cue by rats. Our findings suggest involvement of the endocannabinoid system in the mediation of optimistic judgement bias. PMID:26363193
Interloper bias in future large-scale structure surveys
Pullen, Anthony R; Dore, Olivier; Raccanelli, Alvise
2015-01-01
Next-generation spectroscopic surveys will map the large-scale structure of the observable universe, using emission line galaxies as tracers. While each survey will map the sky with a specific emission line, interloping emission lines can masquerade as the survey's intended emission line at different redshifts. Interloping lines from galaxies that are not removed can contaminate the power spectrum measurement, mixing correlations from various redshifts and diluting the true signal. We assess the potential for power spectrum contamination, finding that an interloper fraction worse than 0.2% could bias power spectrum measurements for future surveys by more than 10% of statistical errors, while also biasing inferences based on the power spectrum. We also construct a formalism for predicting biases for cosmological parameter measurements, and we demonstrate that a 0.3% interloper fraction could bias measurements of the growth rate by more than 10% of the error, which can affect constraints from upcoming surveys o...
International Nuclear Information System (INIS)
From Cosmos to Chaos- Peter Coles, 2006, Oxford University Press, 224pp. To confirm or refute a scientific theory you have to make a measurement. Unfortunately, however, measurements are never perfect: the rest is statistics. Indeed, statistics is at the very heart of scientific progress, but it is often poorly taught and badly received; for many, the very word conjures up half-remembered nightmares of 'null hypotheses' and 'student's t-tests'. From Cosmos to Chaos by Peter Coles, a cosmologist at Nottingham University, is an approachable antidote that places statistics in a range of catchy contexts. Using this book you will be able to calculate the probabilities in a game of bridge or in a legal trial based on DNA fingerprinting, impress friends by talking confidently about entropy, and stretch your mind thinking about quantum mechanics. (U.K.)
Jana, Madhusudan
2015-01-01
Statistical mechanics is self sufficient, written in a lucid manner, keeping in mind the exam system of the universities. Need of study this subject and its relation to Thermodynamics is discussed in detail. Starting from Liouville theorem gradually, the Statistical Mechanics is developed thoroughly. All three types of Statistical distribution functions are derived separately with their periphery of applications and limitations. Non-interacting ideal Bose gas and Fermi gas are discussed thoroughly. Properties of Liquid He-II and the corresponding models have been depicted. White dwarfs and condensed matter physics, transport phenomenon - thermal and electrical conductivity, Hall effect, Magneto resistance, viscosity, diffusion, etc. are discussed. Basic understanding of Ising model is given to explain the phase transition. The book ends with a detailed coverage to the method of ensembles (namely Microcanonical, canonical and grand canonical) and their applications. Various numerical and conceptual problems ar...
Levine-Wissing, Robin
2012-01-01
All Access for the AP® Statistics Exam Book + Web + Mobile Everything you need to prepare for the Advanced Placement® exam, in a study system built around you! There are many different ways to prepare for an Advanced Placement® exam. What's best for you depends on how much time you have to study and how comfortable you are with the subject matter. To score your highest, you need a system that can be customized to fit you: your schedule, your learning style, and your current level of knowledge. This book, and the online tools that come with it, will help you personalize your AP® Statistics prep
Rohatgi, Vijay K
2003-01-01
Unified treatment of probability and statistics examines and analyzes the relationship between the two fields, exploring inferential issues. Numerous problems, examples, and diagrams--some with solutions--plus clear-cut, highlighted summaries of results. Advanced undergraduate to graduate level. Contents: 1. Introduction. 2. Probability Model. 3. Probability Distributions. 4. Introduction to Statistical Inference. 5. More on Mathematical Expectation. 6. Some Discrete Models. 7. Some Continuous Models. 8. Functions of Random Variables and Random Vectors. 9. Large-Sample Theory. 10. General Meth
Mandl, Franz
1988-01-01
The Manchester Physics Series General Editors: D. J. Sandiford; F. Mandl; A. C. Phillips Department of Physics and Astronomy, University of Manchester Properties of Matter B. H. Flowers and E. Mendoza Optics Second Edition F. G. Smith and J. H. Thomson Statistical Physics Second Edition E. Mandl Electromagnetism Second Edition I. S. Grant and W. R. Phillips Statistics R. J. Barlow Solid State Physics Second Edition J. R. Hook and H. E. Hall Quantum Mechanics F. Mandl Particle Physics Second Edition B. R. Martin and G. Shaw The Physics of Stars Second Edition A. C. Phillips Computing for Scient
Davidson, Norman
2003-01-01
Clear and readable, this fine text assists students in achieving a grasp of the techniques and limitations of statistical mechanics. The treatment follows a logical progression from elementary to advanced theories, with careful attention to detail and mathematical development, and is sufficiently rigorous for introductory or intermediate graduate courses.Beginning with a study of the statistical mechanics of ideal gases and other systems of non-interacting particles, the text develops the theory in detail and applies it to the study of chemical equilibrium and the calculation of the thermody
Freund, Rudolf J; Wilson, William J
2010-01-01
Statistical Methods, 3e provides students with a working introduction to statistical methods offering a wide range of applications that emphasize the quantitative skills useful across many academic disciplines. This text takes a classic approach emphasizing concepts and techniques for working out problems and intepreting results. The book includes research projects, real-world case studies, numerous examples and data exercises organized by level of difficulty. This text requires that a student be familiar with algebra. New to this edition: NEW expansion of exercises a
Consequences of Outcome Reporting Bias in Education Research
Williams, R. T.; Polanin, J. R.
2014-01-01
Publication bias is a term that typically refers to the well-known tendency for studies lacking statistically significant results to be less likely to be published in peer-reviewed journals. This happens because authors are less likely to submit, while editors and reviewers are less likely to accept for publication, papers that lack statistically…
Directory of Open Access Journals (Sweden)
Zheng Chunfang
2011-10-01
Full Text Available Abstract Background Paralog reduction, the loss of duplicate genes after whole genome duplication (WGD is a pervasive process. Whether this loss proceeds gene by gene or through deletion of multi-gene DNA segments is controversial, as is the question of fractionation bias, namely whether one homeologous chromosome is more vulnerable to gene deletion than the other. Results As a null hypothesis, we first assume deletion events, on one homeolog only, excise a geometrically distributed number of genes with unknown mean µ, and these events combine to produce deleted runs of length l, distributed approximately as a negative binomial with unknown parameter r, itself a random variable with distribution π(·. A more realistic model requires deletion events on both homeologs distributed as a truncated geometric. We simulate the distribution of run lengths l in both models, as well as the underlying π(r, as a function of µ, and show how sampling l allows us to estimate µ. We apply this to data on a total of 15 genomes descended from 6 distinct WGD events and show how to correct the bias towards shorter runs caused by genome rearrangements. Because of the difficulty in deriving π(· analytically, we develop a deterministic recurrence to calculate each π(r as a function of µ and the proportion of unreduced paralog pairs. Conclusions The parameter µ can be estimated based on run lengths of single-copy regions. Estimates of µ in real data do not exclude the possibility that duplicate gene deletion is largely gene by gene, although it may sometimes involve longer segments.
Chicot, Katie; Holmes, Hilary
2012-01-01
The use, and misuse, of statistics is commonplace, yet in the printed format data representations can be either over simplified, supposedly for impact, or so complex as to lead to boredom, supposedly for completeness and accuracy. In this article the link to the video clip shows how dynamic visual representations can enliven and enhance the…
Bergère, M. C.
1999-01-01
We improve Haldane's formula which gives the number of configurations for $N$ particles on $d$ states in a fractional statistic defined by the coupling $g=l/m$. Although nothing is changed in the thermodynamic limit, the new formula makes sense for finite $N=pm+r$ with $p$ integer and $0
Cognitive Bias in Systems Verification
Larson, Steve
2012-01-01
Working definition of cognitive bias: Patterns by which information is sought and interpreted that can lead to systematic errors in decisions. Cognitive bias is used in diverse fields: Economics, Politics, Intelligence, Marketing, to name a few. Attempts to ground cognitive science in physical characteristics of the cognitive apparatus exceed our knowledge. Studies based on correlations; strict cause and effect is difficult to pinpoint. Effects cited in the paper and discussed here have been replicated many times over, and appear sound. Many biases have been described, but it is still unclear whether they are all distinct. There may only be a handful of fundamental biases, which manifest in various ways. Bias can effect system verification in many ways . Overconfidence -> Questionable decisions to deploy. Availability -> Inability to conceive critical tests. Representativeness -> Overinterpretation of results. Positive Test Strategies -> Confirmation bias. Debiasing at individual level very difficult. The potential effect of bias on the verification process can be managed, but not eliminated. Worth considering at key points in the process.
Administrative bias in South Africa
Directory of Open Access Journals (Sweden)
E S Nwauche
2005-01-01
Full Text Available This article reviews the interpretation of section 6(2(aii of the Promotion of Administrative Justice Act which makes an administrator “biased or reasonably suspected of bias” a ground of judicial review. In this regard, the paper reviews the determination of administrative bias in South Africa especially highlighting the concept of institutional bias. The paper notes that inspite of the formulation of the bias ground of review the test for administrative bias is the reasonable apprehension test laid down in the case of President of South Africa v South African Rugby Football Union(2 which on close examination is not the same thing. Accordingly the paper urges an alternative interpretation that is based on the reasonable suspicion test enunciated in BTR Industries South Africa (Pty Ltd v Metal and Allied Workers Union and R v Roberts. Within this context, the paper constructs a model for interpreting the bias ground of review that combines the reasonable suspicion test as interpreted in BTR Industries and R v Roberts, the possibility of the waiver of administrative bias, the curative mechanism of administrative appeal as well as some level of judicial review exemplified by the jurisprudence of article 6(1 of the European Convention of Human Rights, especially in the light of the contemplation of the South African Magistrate Court as a jurisdictional route of judicial review.
Biased galaxy formation and large-scale structure
Berlind, Andreas Alan
The biased relation between the galaxy and mass distributions lies at the intersection of large scale structure in the universe and the process of galaxy formation. I study the nature of galaxy bias and its connections to galaxy clustering and galaxy formation physics. Galaxy bias has traditionally been viewed as an obstacle to constraining cosmological parameters by studying galaxy clustering. I examine the effect of bias on measurements of the cosmological density parameter Wm by techniques that exploit the gravity-induced motions of galaxies. Using a variety of environmental bias models applied to N-body simulations, I find that, in most cases, the quantity estimated by these techniques is the value of W0.6m/bs , where bs is the ratio of rms galaxy fluctuations to rms mass fluctuations on large scales. Moreover, I find that different methods should, in principle, agree with each other and it is thus unlikely that non-linear or scale-dependent bias is responsible for the discrepancies that exist among current measurements. One can also view the influence of bias on galaxy clustering as a strength rather than a weakness, since it provides us with a potentially powerful way to constrain galaxy formation theories. With this goal in mind, I develop the "Halo Occupation Distribution" (HOD), a physically motivated and complete formulation of bias that is based on the distribution of galaxies within virialized dark matter halos. I explore the sensitivity of galaxy clustering statistics to features of the HOD and focus on how the HOD may be empirically constrained from galaxy clustering data. I make the connection to the physics of galaxy formation by studying the HOD predicted by the two main theoretical methods of modeling galaxy formation. I find that, despite many differences between them, the two methods predict the same HOD, suggesting that galaxy bias is determined by robust features of the hierarchical galaxy formation process rather than details of gas cooling
Sources of bias in single-trial normalization procedures.
Ciuparu, Andrei; Mureşan, Raul C
2016-04-01
Baseline normalization procedures are essential for the analysis of brain activity. These use statistics of a reference (baseline) period to normalize data along the entire trial (baseline and stimulus periods). A very popular procedure is pseudo z-scoring, traditionally applied to time-frequency spectral power estimates, where it was recently shown to generate positive bias. Bias was thought to arise because of outliers stemming from the skewed distribution of spectral power values. Here we challenge this view and causally show that bias originates from a more general problem that affects a wide array of normalization techniques, including some that are routinely used. We show that bias is caused by the division of correlated terms and that it depends directly on the sign and magnitude of correlation between the numerator and denominator. Correlation emerges either from the properties of the data being normalized or from the properties of the normalization method. z-scoring produces bias when source data have a skewed distribution but it is bias-free when the distribution is symmetric, while methods such as dF/F for fluorescence data lead to bias because the numerator and denominator are inherently correlated. We provide a simple, fast and general solution to reduce and even eliminate bias by welding (fusing) baseline periods of multiple trials into a single, large baseline. This method is generic, can be used to normalize individual trials and provides bias-free estimates given a long enough extended baseline. We show that baseline fusing is superior to more complex techniques that have been proposed before. PMID:26797876
Statistics of statistical anisotropy measures
International Nuclear Information System (INIS)
Cosmic Microwave Background (CMB) is a Gaussian random field to a sufficient approximation, and its statistics is completely specified by the 2-point correlation function, which, most generally, can be expanded in Bipolar Spherical Harmonic (BipoSH) basis. Statistical Isotropy (SI) of 2-point correlation function is a common assumption in cosmology, which needs to be tested. Any SI violating signal can be searched in the expansion BipoSH coefficients. We have analytically evaluated the moments and the distribution of these coefficients using characteristic function approach. We have found that coefficients with M = 0 have an exact analytical form for any order moment. For the remaining BipoSH coefficients with M ≠ 0, the moments have to be supplemented with a correction term. We have verified our results with measurements of BipoSH coefficients on numerically simulated statistically isotropic CMB maps
Schematic for efficient computation of GC, GC3, and AT3 bias spectra of genome.
Rizvi, Ahsan Z; Venu Gopal, T; Bhattacharya, C
2012-01-01
Selection of synonymous codons for an amino acid is biased in protein translation process. This biased selection causes repetition of synonymous codons in structural parts of genome that stands for high N/3 peaks in DNA spectrum. Period-3 spectral property is utilized here to produce a 3-phase network model based on polyphase filterbank concepts for derivation of codon bias spectra (CBS). Modification of parameters in this model can produce GC, GC3, and AT3 bias spectra. Complete schematic in LabVIEW platform is presented here for efficient and parallel computation of GC, GC3, and AT3 bias spectra of genomes alongwith results of CBS patterns. We have performed the correlation coefficient analysis of GC, GC3, and AT3 bias spectra with codon bias patterns of CBS for biological and statistical significance of this model. PMID:22368390
Hsu, Hsiao-Ping; Nadler, Walder; Grassberger, Peter
2005-07-01
The scaling behavior of randomly branched polymers in a good solvent is studied in two to nine dimensions, modeled by lattice animals on simple hypercubic lattices. For the simulations, we use a biased sequential sampling algorithm with re-sampling, similar to the pruned-enriched Rosenbluth method (PERM) used extensively for linear polymers. We obtain high statistics of animals with up to several thousand sites in all dimension 2⩽d⩽9. The partition sum (number of different animals) and gyration radii are estimated. In all dimensions we verify the Parisi-Sourlas prediction, and we verify all exactly known critical exponents in dimensions 2, 3, 4, and ⩾8. In addition, we present the hitherto most precise estimates for growth constants in d⩾3. For clusters with one site attached to an attractive surface, we verify the superuniversality of the cross-over exponent at the adsorption transition predicted by Janssen and Lyssy.
Publication Bias in Meta-Analyses of the Efficacy of Psychotherapeutic Interventions for Depression
Niemeyer, Helen; Musch, Jochen; Pietrowsky, Reinhard
2013-01-01
Objective: The aim of this study was to assess whether systematic reviews investigating psychotherapeutic interventions for depression are affected by publication bias. Only homogeneous data sets were included, as heterogeneous data sets can distort statistical tests of publication bias. Method: We applied Begg and Mazumdar's adjusted rank…
International Nuclear Information System (INIS)
For the years 1992 and 1993, part of the figures shown in the tables of the Energy Review are preliminary or estimated. The annual statistics of the Energy Review appear in more detail from the publication Energiatilastot - Energy Statistics issued annually, which also includes historical time series over a longer period. The tables and figures shown in this publication are: Changes in the volume of GNP and energy consumption; Coal consumption; Natural gas consumption; Peat consumption; Domestic oil deliveries; Import prices of oil; Price development of principal oil products; Fuel prices for power production; Total energy consumption by source; Electricity supply; Energy imports by country of origin in 1993; Energy exports by recipient country in 1993; Consumer prices of liquid fuels; Consumer prices of hard coal and natural gas, prices of indigenous fuels; Average electricity price by type of consumer; Price of district heating by type of consumer and Excise taxes and turnover taxes included in consumer prices of some energy sources
Goodman, Joseph W.
2000-07-01
The Wiley Classics Library consists of selected books that have become recognized classics in their respective fields. With these new unabridged and inexpensive editions, Wiley hopes to extend the life of these important works by making them available to future generations of mathematicians and scientists. Currently available in the Series: T. W. Anderson The Statistical Analysis of Time Series T. S. Arthanari & Yadolah Dodge Mathematical Programming in Statistics Emil Artin Geometric Algebra Norman T. J. Bailey The Elements of Stochastic Processes with Applications to the Natural Sciences Robert G. Bartle The Elements of Integration and Lebesgue Measure George E. P. Box & Norman R. Draper Evolutionary Operation: A Statistical Method for Process Improvement George E. P. Box & George C. Tiao Bayesian Inference in Statistical Analysis R. W. Carter Finite Groups of Lie Type: Conjugacy Classes and Complex Characters R. W. Carter Simple Groups of Lie Type William G. Cochran & Gertrude M. Cox Experimental Designs, Second Edition Richard Courant Differential and Integral Calculus, Volume I RIchard Courant Differential and Integral Calculus, Volume II Richard Courant & D. Hilbert Methods of Mathematical Physics, Volume I Richard Courant & D. Hilbert Methods of Mathematical Physics, Volume II D. R. Cox Planning of Experiments Harold S. M. Coxeter Introduction to Geometry, Second Edition Charles W. Curtis & Irving Reiner Representation Theory of Finite Groups and Associative Algebras Charles W. Curtis & Irving Reiner Methods of Representation Theory with Applications to Finite Groups and Orders, Volume I Charles W. Curtis & Irving Reiner Methods of Representation Theory with Applications to Finite Groups and Orders, Volume II Cuthbert Daniel Fitting Equations to Data: Computer Analysis of Multifactor Data, Second Edition Bruno de Finetti Theory of Probability, Volume I Bruno de Finetti Theory of Probability, Volume 2 W. Edwards Deming Sample Design in Business Research
B. G. Sidharth
2000-01-01
We consider the recent description of elementary particles in terms of Quantum Mechanical Kerr-Newman Black Holes, a description which provides a rationale for and at the same time reconciles the Bohm-hydrodynamical formulation on the one hand and the Nelsonian stochastiic formulation on the other. The Boson-Fermion divide is discussed, and it is pointed out that in special situations, anomalous statistics, rather than Bose-Einstein or Fermi-Dirac states, can be encountered.
Vardeman, Stephen B.
2003-01-01
In this entry we seek to put into perspective some of the ways in which statistical methods contribute to modern engineering practice. Engineers design and oversee the production, operation, and maintenance of the products and systems that under-gird modern technological society. Their work is built on the foundation of physical (and increasingly biological) science. However, it is of necessity often highly empirical, because there simply isnt scientific theory complete and simple enough to ...
Nicodème, Pierre; Salvy, Bruno; Flajolet, Philippe
1999-01-01
We present a complete analysis of the statistics of number of occurrences of a regular expression pattern in a random text. This covers «motifs» widely used in computational biology. Our approach is based on: (i) a constructive approach to classical results in theoretical computer science (automata and formal language theory), in particular, the rationality of generating functions of regular languages; (ii) analytic combinatorics that is used for deriving asymptotic properties from generating...
Natrella, Mary Gibbons
2005-01-01
Formulated to assist scientists and engineers engaged in army ordnance research and development programs, this well-known and highly regarded handbook is a ready reference for advanced undergraduate and graduate students as well as for professionals seeking engineering information and quantitative data for designing, developing, constructing, and testing equipment. Topics include characterizing and comparing the measured performance of a material, product, or process; general considerations in planning experiments; statistical techniques for analyzing extreme-value data; use of transformations
Cognitive biases and language universals
Baronchelli, Andrea; Puglisi, Andrea
2013-01-01
Language universals have been longly attributed to an innate Universal Grammar. An alternative explanation states that linguistic universals emerged independently in every language in response to shared cognitive, though non language-specific, biases. A computational model has recently shown how this could be the case, focusing on the paradigmatic example of the universal properties of color naming patterns, and producing results in accurate agreement with the experimental data. Here we investigate thoroughly the role of a cognitive bias in the framework of this model. We study how, and to what extent, the structure of the bias can influence the corresponding linguistic universal patterns. We show also that the cultural history of a group of speakers introduces population-specific constraints that act against the uniforming pressure of the cognitive bias, and we clarify the interplay between these two forces. We believe that our simulations can help to shed light on the possible mechanisms at work in the evol...
Meneghetti, M; Dahle, H; Limousin, M
2013-01-01
The existence of an arc statistics problem was at the center of a strong debate in the last fifteen years. With the aim to clarify if the optical depth for giant gravitational arcs by galaxy clusters in the so called concordance model is compatible with observations, several studies were carried out which helped to significantly improve our knowledge of strong lensing clusters, unveiling their extremely complex internal structure. In particular, the abundance and the frequency of strong lensing events like gravitational arcs turned out to be a potentially very powerful tool to trace the structure formation. However, given the limited size of observational and theoretical data-sets, the power of arc statistics as a cosmological tool has been only minimally exploited so far. On the other hand, the last years were characterized by significant advancements in the field, and several cluster surveys that are ongoing or planned for the near future seem to have the potential to make arc statistics a competitive cosmo...
Cognitive biases, linguistic universals, and constraint-based grammar learning.
Culbertson, Jennifer; Smolensky, Paul; Wilson, Colin
2013-07-01
According to classical arguments, language learning is both facilitated and constrained by cognitive biases. These biases are reflected in linguistic typology-the distribution of linguistic patterns across the world's languages-and can be probed with artificial grammar experiments on child and adult learners. Beginning with a widely successful approach to typology (Optimality Theory), and adapting techniques from computational approaches to statistical learning, we develop a Bayesian model of cognitive biases and show that it accounts for the detailed pattern of results of artificial grammar experiments on noun-phrase word order (Culbertson, Smolensky, & Legendre, 2012). Our proposal has several novel properties that distinguish it from prior work in the domains of linguistic theory, computational cognitive science, and machine learning. This study illustrates how ideas from these domains can be synthesized into a model of language learning in which biases range in strength from hard (absolute) to soft (statistical), and in which language-specific and domain-general biases combine to account for data from the macro-level scale of typological distribution to the micro-level scale of learning by individuals. PMID:23703887
Preferences, country bias, and international trade
S. Roy (Santanu); J.M.A. Viaene (Jean-Marie)
1998-01-01
textabstractAnalyzes international trade where consumer preferences exhibit country bias. Why country biases arise; How trade can occur in the presence of country bias; Implication for the pattern of trade and specialization.
Detecting and Punishing Unconscious Bias
Tetlock, Philip E; Gregory Mitchell; L. Jason Anastasopoulos
2013-01-01
We present experimental results demonstrating how ideology shapes evaluations of technology aimed at detecting unconscious biases: (1) liberals supported use of the technology to detect unconscious racism but not unconscious anti-Americanism, whereas conservatives showed the reverse pattern, (2) liberals and conservatives opposed punishing individuals for unconscious bias but supported punishing organizations failing to use the technology to root out, respectively, racism or anti-Americanism,...
The intentionality bias and schizotypy
Moore, James W.; Pope, A.
2014-01-01
The “intentionality bias” refers to our automatic tendency to judge other people's actions to be intentional. In this experiment we extended research on this effect in two key ways. First, we developed a novel nonlinguistic task for assessing the intentionality bias. This task used video stimuli of ambiguous movements. Second, we investigated the relationship between the strength of this bias and schizotypy (schizophrenia-like symptoms in healthy individuals). Our results showed that the inte...
Measuring statistical evidence using relative belief.
Evans, Michael
2016-01-01
A fundamental concern of a theory of statistical inference is how one should measure statistical evidence. Certainly the words "statistical evidence," or perhaps just "evidence," are much used in statistical contexts. It is fair to say, however, that the precise characterization of this concept is somewhat elusive. Our goal here is to provide a definition of how to measure statistical evidence for any particular statistical problem. Since evidence is what causes beliefs to change, it is proposed to measure evidence by the amount beliefs change from a priori to a posteriori. As such, our definition involves prior beliefs and this raises issues of subjectivity versus objectivity in statistical analyses. This is dealt with through a principle requiring the falsifiability of any ingredients to a statistical analysis. These concerns lead to checking for prior-data conflict and measuring the a priori bias in a prior. PMID:26925207
The ergodicity bias in the observed galaxy distribution
Pan, Jun
2010-01-01
The spatial distribution of galaxies we observed is subject to the given condition that we, human beings are sitting right in a galaxy -- the Milky Way. Thus the ergodicity assumption is questionable in interpretation of the observed galaxy distribution. The difference between observed statistics (volume average) and the true cosmic value (ensemble average), which we term as the ergodicity bias, is not a trivia quantity and may become significant systematics to statistical analysis of large scale structure and precision cosmology. We numerically evaluate the effect for a set of survey depth and near-end distance cut and find that the ergodicity bias in observed two- and three-point correlation functions can indeed become non-negligible in some cases, especially for the three-point correlation function. One has to take extra care in galaxy sample construction and interpretation of the statistics of the sample, especially when the characteristic redshift is low.
The estimation method of GPS instrumental biases
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
A model of estimating the global positioning system (GPS) instrumental biases and the methods to calculate the relative instrumental biases of satellite and receiver are presented. The calculated results of GPS instrumental biases, the relative instrumental biases of satellite and receiver, and total electron content (TEC) are also shown. Finally, the stability of GPS instrumental biases as well as that of satellite and receiver instrumental biases are evaluated, indicating that they are very stable during a period of two months and a half.
Statistical properties of randomization in clinical trials.
Lachin, J M
1988-12-01
This is the first of five articles on the properties of different randomization procedures used in clinical trials. This paper presents definitions and discussions of the statistical properties of randomization procedures as they relate to both the design of a clinical trial and the statistical analysis of trial results. The subsequent papers consider, respectively, the properties of simple (complete), permuted-block (i.e., blocked), and urn (adaptive biased-coin) randomization. The properties described herein are the probabilities of treatment imbalances and the potential effects on the power of statistical tests; the permutational basis for statistical tests; and the potential for experimental biases in the assessment of treatment effects due either to the predictability of the random allocations (selection bias) or the susceptibility of the randomization procedure to covariate imbalances (accidental bias). For most randomization procedures, the probabilities of overall treatment imbalances are readily computed, even when a stratified randomization is used. This is important because treatment imbalance may affect statistical power. It is shown, however, that treatment imbalance must be substantial before power is more than trivially affected. The differences between a population versus a permutation model as a basis for a statistical test are reviewed. It is argued that a population model can only be invoked in clinical trials as an untestable assumption, rather than being formally based on sampling at random from a population. On the other hand, a permutational analysis based on the randomization actually employed requires no assumptions regarding the origin of the samples of patients studied. The large sample permutational distribution of the family of linear rank tests is described as a basis for easily conducting a variety of permutation tests. Subgroup (stratified) analyses, analyses when some data are missing, and regression model analyses are also
Bias and design in software specifications
Straub, Pablo A.; Zelkowitz, Marvin V.
1990-01-01
Implementation bias in a specification is an arbitrary constraint in the solution space. Presented here is a model of bias in software specifications. Bias is defined in terms of the specification process and a classification of the attributes of the software product. Our definition of bias provides insight into both the origin and the consequences of bias. It also shows that bias is relative and essentially unavoidable. Finally, we describe current work on defining a measure of bias, formalizing our model, and relating bias to software defects.
A MORET tool to assist code bias estimation
International Nuclear Information System (INIS)
This new Graphical User Interface (GUI) developed in JAVA is one of the post-processing tools for MORET4 code. It aims to help users to estimate the importance of the keff bias due to the code in order to better define the upper safety limit. Moreover, it allows visualizing the distance between an actual configuration case and evaluated critical experiments. This tool depends on a validated experiments database, on sets of physical parameters and on various statistical tools allowing interpolating the calculation bias of the database or displaying the projections of experiments on a reduced base of parameters. The development of this tool is still in progress. (author)
1986-01-01
Official population data for the USSR are presented for 1985 and 1986. Part 1 (pp. 65-72) contains data on capitals of union republics and cities with over one million inhabitants, including population estimates for 1986 and vital statistics for 1985. Part 2 (p. 72) presents population estimates by sex and union republic, 1986. Part 3 (pp. 73-6) presents data on population growth, including birth, death, and natural increase rates, 1984-1985; seasonal distribution of births and deaths; birth order; age-specific birth rates in urban and rural areas and by union republic; marriages; age at marriage; and divorces. PMID:12178831
Negativity Bias in Dangerous Drivers.
Chai, Jing; Qu, Weina; Sun, Xianghong; Zhang, Kan; Ge, Yan
2016-01-01
The behavioral and cognitive characteristics of dangerous drivers differ significantly from those of safe drivers. However, differences in emotional information processing have seldom been investigated. Previous studies have revealed that drivers with higher anger/anxiety trait scores are more likely to be involved in crashes and that individuals with higher anger traits exhibit stronger negativity biases when processing emotions compared with control groups. However, researchers have not explored the relationship between emotional information processing and driving behavior. In this study, we examined the emotional information processing differences between dangerous drivers and safe drivers. Thirty-eight non-professional drivers were divided into two groups according to the penalty points that they had accrued for traffic violations: 15 drivers with 6 or more points were included in the dangerous driver group, and 23 drivers with 3 or fewer points were included in the safe driver group. The emotional Stroop task was used to measure negativity biases, and both behavioral and electroencephalograph data were recorded. The behavioral results revealed stronger negativity biases in the dangerous drivers than in the safe drivers. The bias score was correlated with self-reported dangerous driving behavior. Drivers with strong negativity biases reported having been involved in mores crashes compared with the less-biased drivers. The event-related potentials (ERPs) revealed that the dangerous drivers exhibited reduced P3 components when responding to negative stimuli, suggesting decreased inhibitory control of information that is task-irrelevant but emotionally salient. The influence of negativity bias provides one possible explanation of the effects of individual differences on dangerous driving behavior and traffic crashes. PMID:26765225
Kurant, Maciej; Thiran, Patrick
2010-01-01
Breadth First Search (BFS) and other graph traversal techniques are widely used for measuring large unknown graphs, such as online social networks. It has been empirically observed that an incomplete BFS is biased toward high degree nodes. In contrast to more studied sampling techniques, such as random walks, the precise bias of BFS has not been characterized to date. In this paper, we quantify the degree bias of BFS sampling. In particular, we calculate the node degree distribution expected to be observed by BFS as a function of the fraction of covered nodes, in a random graph $RG(p_k)$ with a given degree distribution $p_k$. Furthermore, we also show that, for $RG(p_k)$, all commonly used graph traversal techniques (BFS, DFS, Forest Fire, and Snowball Sampling) lead to the same bias, and we show how to correct for this bias. To give a broader perspective, we compare this class of exploration techniques to random walks that are well-studied and easier to analyze. Next, we study by simulation the effect of gr...
Modeling late entry bias in survival analysis.
Matsuura, Masaaki; Eguchi, Shinto
2005-06-01
In a failure time analysis, we sometimes observe additional study subjects who enter during the study period. These late entries are treated as left-truncated data in the statistical literature. However, with real data, there is a substantial possibility that the delayed entries may have extremely different hazards compared to the other standard subjects. We focus on a situation in which such entry bias might arise in the analysis of survival data. The purpose of the present article is to develop an appropriate methodology for making inference about data including late entries. We construct a model that includes parameters for the effect of delayed entry bias having no specification for the distribution of entry time. We also discuss likelihood inference based on this model and derive the asymptotic behavior of estimates. A simulation study is conducted for a finite sample size in order to compare the analysis results using our method with those using the standard method, where independence between entry time and failure time is assumed. We apply this method to mortality analysis among atomic bomb survivors defined in a geographical study region. PMID:16011705
Measurement Bias Detection through Factor Analysis
Barendse, M. T.; Oort, F. J.; Werner, C. S.; Ligtvoet, R.; Schermelleh-Engel, K.
2012-01-01
Measurement bias is defined as a violation of measurement invariance, which can be investigated through multigroup factor analysis (MGFA), by testing across-group differences in intercepts (uniform bias) and factor loadings (nonuniform bias). Restricted factor analysis (RFA) can also be used to detect measurement bias. To also enable nonuniform…
Inference for blocked randomization under a selection bias model.
Kennes, Lieven N; Rosenberger, William F; Hilgers, Ralf-Dieter
2015-12-01
We provide an asymptotic test to analyze randomized clinical trials that may be subject to selection bias. For normally distributed responses, and under permuted block randomization, we derive a likelihood ratio test of the treatment effect under a selection bias model. A likelihood ratio test of the presence of selection bias arises from the same formulation. We prove that the test is asymptotically chi-square on one degree of freedom. These results correlate well with the likelihood ratio test of Ivanova et al. (2005, Statistics in Medicine 24, 1537-1546) for binary responses, for which they established by simulation that the asymptotic distribution is chi-square. Simulations also show that the test is robust to departures from normality and under another randomization procedure. We illustrate the test by reanalyzing a clinical trial on retinal detachment. PMID:26099068
Excess success for three related papers on racial bias.
Francis, Gregory
2015-01-01
Three related articles reported that racial bias altered perceptual experience and influenced decision-making. These findings have been applied to training programs for law enforcement, and elsewhere, to mitigate racial bias. However, a statistical analysis of each of the three articles finds that the reported experimental results should be rare, even if the theoretical ideas were correct. The analysis estimates that the probability of the reported experimental success for the articles is 0.003, 0.048, and 0.070, respectively. These low probabilities suggest that similar future work is unlikely to produce as successful outcomes and indicates that readers should be skeptical about the validity of the reported findings and their theoretical implications. The reported findings should not be used to guide policies related to racial bias, and new experimental work is needed to judge the merit of the theoretical ideas. PMID:25983701
Excess success for three related papers on racial bias
Directory of Open Access Journals (Sweden)
Gregory eFrancis
2015-05-01
Full Text Available Three related articles reported that racial bias altered perceptual experience and influenced decision-making. These findings have been applied to training programs for law enforcement, and elsewhere, to mitigate racial bias. However, a statistical analysis of each of the three articles finds that the reported experimental results should be rare, even if the theoretical ideas were correct. The analysis estimates that the probability of the reported experimental success for the articles is 0.003, 0.048, and 0.070, respectively. These low probabilities suggest that similar future work is unlikely to produce as successful outcomes and indicates that readers should be skeptical about the validity of the reported findings and their theoretical implications. The reported findings should not be used to guide policies related to racial bias, and new experimental work is needed to judge the merit of the theoretical ideas.
Biagetti, Matteo; Kehagias, Alex; Riotto, Antonio
2014-01-01
It has been recently shown that any halo velocity bias present in the initial conditions does not decay to unity, in agreement with predictions from peak theory. However, this is at odds with the standard formalism based on the coupled fluids approximation for the coevolution of dark matter and halos. Starting from conservation laws in phase space, we discuss why the fluid momentum conservation equation for the biased tracers needs to be modified in accordance with the change advocated in Baldauf, Desjacques & Seljak (2014). Our findings indicate that a correct description of the halo properties should properly take into account peak constraints when starting from the Vlasov-Boltzmann equation.
Saito, Shun; Vlah, Zvonimir; Seljak, Uroš; Okumura, Teppei; McDonald, Patrick
2014-01-01
Understanding the relation between underlying matter distribution and biased tracers such as galaxy or dark matter halo is essential to extract cosmological information from ongoing or future galaxy redshift surveys. At sufficiently large scales such as the BAO scale, a standard approach for the bias problem on the basis of the perturbation theory (PT) is to assume the `local bias' model in which the density field of biased tracers is deterministically expanded in terms of matter density field at the same position. The higher-order bias parameters are then determined by combining the power spectrum with higher-order statistics such as the bispectrum. As is pointed out by recent studies, however, nonlinear gravitational evolution naturally induces nonlocal bias terms even if initially starting only with purely local bias. As a matter of fact, previous works showed that the second-order nonlocal bias term, which corresponds to the gravitational tidal field, is important to explain the characteristic scale-depen...
Longman, Richard W.; Bergmann, Martin; Juang, Jer-Nan
1988-01-01
For the ERA system identification algorithm, perturbation methods are used to develop expressions for variance and bias of the identified modal parameters. Based on the statistics of the measurement noise, the variance results serve as confidence criteria by indicating how likely the true parameters are to lie within any chosen interval about their identified values. This replaces the use of expensive and time-consuming Monte Carlo computer runs to obtain similar information. The bias estimates help guide the ERA user in his choice of which data points to use and how much data to use in order to obtain the best results, performing the trade-off between the bias and scatter. Also, when the uncertainty in the bias is sufficiently small, the bias information can be used to correct the ERA results. In addition, expressions for the variance and bias of the singular values serve as tools to help the ERA user decide the proper modal order.
Bias in the physical examination of patients with lumbar radiculopathy
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Katz Jeffrey N
2010-11-01
Full Text Available Abstract Background No prior studies have examined systematic bias in the musculoskeletal physical examination. The objective of this study was to assess the effects of bias due to prior knowledge of lumbar spine magnetic resonance imaging findings (MRI on perceived diagnostic accuracy of the physical examination for lumbar radiculopathy. Methods This was a cross-sectional comparison of the performance characteristics of the physical examination with blinding to MRI results (the 'independent group' with performance in the situation where the physical examination was not blinded to MRI results (the 'non-independent group'. The reference standard was the final diagnostic impression of nerve root impingement by the examining physician. Subjects were recruited from a hospital-based outpatient specialty spine clinic. All adults age 18 and older presenting with lower extremity radiating pain of duration ≤ 12 weeks were evaluated for participation. 154 consecutively recruited subjects with lumbar disk herniation confirmed by lumbar spine MRI were included in this study. Sensitivities and specificities with 95% confidence intervals were calculated in the independent and non-independent groups for the four components of the radiculopathy examination: 1 provocative testing, 2 motor strength testing, 3 pinprick sensory testing, and 4 deep tendon reflex testing. Results The perceived sensitivity of sensory testing was higher with prior knowledge of MRI results (20% vs. 36%; p = 0.05. Sensitivities and specificities for exam components otherwise showed no statistically significant differences between groups. Conclusions Prior knowledge of lumbar MRI results may introduce bias into the pinprick sensory testing component of the physical examination for lumbar radiculopathy. No statistically significant effect of bias was seen for other components of the physical examination. The effect of bias due to prior knowledge of lumbar MRI results should be considered
A novel bias correction methodology for climate impact simulations
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S. Sippel
2015-10-01
Full Text Available Understanding, quantifying and attributing the impacts of extreme weather and climate events in the terrestrial biosphere is crucial for societal adaptation in a changing climate. However, climate model simulations generated for this purpose typically exhibit biases in their output that hinders any straightforward assessment of impacts. To overcome this issue, various bias correction strategies are routinely used to alleviate climate model deficiencies most of which have been criticized for physical inconsistency and the non-preservation of the multivariate correlation structure. In this study, we introduce a novel, resampling-based bias correction scheme that fully preserves the physical consistency and multivariate correlation structure of the model output. This procedure strongly improves the representation of climatic extremes and variability in a large regional climate model ensemble (HadRM3P, climateprediction.net/weatherathome, which is illustrated for summer extremes in temperature and rainfall over Central Europe. Moreover, we simulate biosphere–atmosphere fluxes of carbon and water using a terrestrial ecosystem model (LPJmL driven by the bias corrected climate forcing. The resampling-based bias correction yields strongly improved statistical distributions of carbon and water fluxes, including the extremes. Our results thus highlight the importance to carefully consider statistical moments beyond the mean for climate impact simulations. In conclusion, the present study introduces an approach to alleviate climate model biases in a physically consistent way and demonstrates that this yields strongly improved simulations of climate extremes and associated impacts in the terrestrial biosphere. A wider uptake of our methodology by the climate and impact modelling community therefore seems desirable for accurately quantifying past, current and future extremes.
Bias in Dynamic Monte Carlo Alpha Calculations
Energy Technology Data Exchange (ETDEWEB)
Sweezy, Jeremy Ed [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Nolen, Steven Douglas [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Adams, Terry R. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Trahan, Travis John [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2015-02-06
A 1/N bias in the estimate of the neutron time-constant (commonly denoted as α) has been seen in dynamic neutronic calculations performed with MCATK. In this paper we show that the bias is most likely caused by taking the logarithm of a stochastic quantity. We also investigate the known bias due to the particle population control method used in MCATK. We conclude that this bias due to the particle population control method is negligible compared to other sources of bias.
Non-local bias contribution to third-order galaxy correlations
Bel, J.; Hoffmann, K.; Gaztañaga, E.
2015-10-01
We study halo clustering bias with second- and third-order statistics of halo and matter density fields in the Marenostrum Institut de Ciències de l'Espai (MICE) Grand Challenge simulation. We verify that two-point correlations deliver reliable estimates of the linear bias parameters at large scales, while estimations from the variance can be significantly affected by non-linear and possibly non-local contributions to the bias function. Combining three-point auto- and cross-correlations we find, for the first time in configuration space, evidence for the presence of such non-local contributions. These contributions are consistent with predicted second-order non-local effects on the bias functions originating from the dark matter tidal field. Samples of massive haloes show indications of bias (local or non-local) beyond second order. Ignoring non-local bias causes 20-30 and 5-10 per cent overestimation of the linear bias from three-point auto- and cross-correlations, respectively. We study two third-order bias estimators that are not affected by second-order non-local contributions. One is a combination of three-point auto- and cross-correlations. The other is a combination of third-order one- and two-point cumulants. Both methods deliver accurate estimations of the linear bias. Ignoring non-local bias causes higher values of the second-order bias from three-point correlations. Our results demonstrate that third-order statistics can be employed for breaking the growth-bias degeneracy.
Microturbulence measurements during divertor biasing
International Nuclear Information System (INIS)
The application of a bias voltage to a neutralization plate of the upper divertor with respect to the vacuum chamber in the Tokamak de Varennes (TdeV) influences the plasma well inside the separatrix. In particular, the unbiased Ohmic poloidal rotation edge velocity measured by visible spectroscopy is found to be in the electron diamagnetic drift direction (2-3 km/s) and increases by a factor of two for Vbias = 100 V. This coincides with a major reduction of the microturbulence signal at low frequencies (50 kHz -1 -1), as determined from coherent laser scattering measurements. One possible explanation is that the turbulence signal is simply Doppler shifted to frequencies outside the accessible range. This scenario is, however, difficult to reconcile with some observations. Another explanation invokes a reduction of the turbulence level. The variation of the turbulence signal as a function of the applied bias voltage can indeed be reproduced with a theoretical model based on radial and poloidal decorrelation mechanisms, the latter corresponding to poloidal velocity shear stabilization. This model also explains the observed steepening of the k-spectrum decay during biasing. Biasing also modifies the electron density profile inside the separatrix. These changes of nabla ne cannot explain the behaviour of microturbulence behaviour, when explained in terms of stabilization, would agree with the plasma maintaining a steeper electron density gradient. (author). 17 refs, 9 figs
Perception bias in route choice
Vreeswijk, J.D.; Thomas, T.; Berkum, van E.C.; Arem, van B.
2014-01-01
Travel time is probably one of the most studied attributes in route choice. Recently, perception of travel time received more attention as several studies have shown its importance in explaining route choice behavior. In particular, travel time estimates by travelers appear to be biased against non-
Bias in Peripheral Depression Biomarkers
DEFF Research Database (Denmark)
Carvalho, André F; Köhler, Cristiano A; Brunoni, André R;
2016-01-01
BACKGROUND: To aid in the differentiation of individuals with major depressive disorder (MDD) from healthy controls, numerous peripheral biomarkers have been proposed. To date, no comprehensive evaluation of the existence of bias favoring the publication of significant results or inflating effect...
International Nuclear Information System (INIS)
Since the restart of the LHC in November 2009, ATLAS has collected inelastic pp collisions to perform first measurements on charged particle densities. These measurements will help to constrain various models describing phenomenologically soft parton interactions. Understanding the trigger efficiencies for different event types are therefore crucial to minimize any possible bias in the event selection. ATLAS uses two main minimum bias triggers, featuring complementary detector components and trigger levels. While a hardware based first trigger level situated in the forward regions with 2.2 < |η| < 3.8 has been proven to select pp-collisions very efficiently, the Inner Detector based minimum bias trigger uses a random seed on filled bunches and central tracking detectors for the event selection. Both triggers were essential for the analysis of kinematic spectra of charged particles. Their performance and trigger efficiency measurements as well as studies on possible bias sources will be presented. We also highlight the advantage of these triggers for particle correlation analyses. (author)
Observer Biases in the Classroom.
Kite, Mary E.
1991-01-01
Presents three student exercises that demonstrate common perceptual errors described in social psychological literature: actor-observer effect, false consensus bias, and priming effects. Describes methods to be followed and gives terms, sentences, and a story to be used in the exercises. Suggests discussion of the bases and impact of such…
Stereotype Formation : Biased by Association
Le Pelley, Mike E.; Reimers, Stian J.; Calvini, Guglielmo; Spears, Russell; Beesley, Tom; Murphy, Robin A.
2010-01-01
We propose that biases in attitude and stereotype formation might arise as a result of learned differences ill the extent its which social groups have previously been predictive elf behavioral or physical properties Experiments 1 and 2 demonstrate that differences in the experienced predictiveness o
Evaluating a Combined Bias Correction and Stochastic Downscaling Method
Volosciuk, Claudia; Maraun, Douglas; Vrac, Mathieu; Widmann, Martin
2016-04-01
Much of our knowledge about future changes in precipitation relies on global (GCM) and/or regional climate models (RCM) that have resolutions which are much coarser than typical spatial scales of extreme precipitation. The major problems with these projections are both climate model biases and the scale gap between grid box and point scale. Wong et al. presented a first attempt to jointly bias correct and downscale precipitation at daily scales. This approach however relied on spectrally nudged RCM simulations and was not able to post-process GCM biases. Previously, we have presented an extension of this approach that separates the downscaling from the bias correction and in principle is applicable to free running RCMs, such as those available from ENSEMBLES or CORDEX. In a first step, we bias correct the RCMs (EURO-CORDEX) against gridded observational datasets (e.g., E-OBS) at the same scale using a quantile mapping approach that relies on distribution transformation. To correct the whole precipitation distribution including extreme tails we apply a mixture distribution of a gamma distribution for the precipitation mass and a generalized Pareto distribution for the extreme tail. In a second step, we bridge the scale gap: we add small scale variability to the bias corrected precipitation time series using a vector generalized linear gamma model (VGLM gamma). To calibrate the VGLM gamma model we determine the statistical relationship between precipitation observations on different scales, i.e. between gridded (e.g., E-OBS) and station (ECA&D) observations. Here we present a comprehensive evaluation of this approach against 86 weather stations in Europe based on the VALUE perfect predictor experiment, including a comparison with standard bias correction techniques.
Separate universe consistency relation and calibration of halo bias
Li, Yin; Hu, Wayne; Takada, Masahiro
2016-03-01
The linear halo bias is the response of the dark matter halo number density to a long-wavelength fluctuation in the dark matter density. Using abundance matching between separate universe simulations which absorb the latter into a change in the background, we test the consistency relation between the change in a one-point function, the halo mass function, and a two-point function, the halo-matter cross-correlation in the long-wavelength limit. We find excellent agreement between the two at the 1%-2% level for average halo biases between 1 ≲b¯ 1≲4 and no statistically significant deviations at the 4%-5% level out to b¯1≈8 . The halo bias inferred assuming instead a universal mass function is significantly different and inaccurate at the 10% level or more. The separate universe technique provides a way of calibrating the linear halo bias efficiently for even highly biased rare halos in the Λ cold dark matter model. Observational violation of the consistency relation would indicate new physics, e.g. in the dark matter, dark energy, or primordial non-Gaussianity sectors.
An assessment of Bayesian bias estimator for numerical weather prediction
Directory of Open Access Journals (Sweden)
J. Son
2008-12-01
Full Text Available Various statistical methods are used to process operational Numerical Weather Prediction (NWP products with the aim of reducing forecast errors and they often require sufficiently large training data sets. Generating such a hindcast data set for this purpose can be costly and a well designed algorithm should be able to reduce the required size of these data sets.
This issue is investigated with the relatively simple case of bias correction, by comparing a Bayesian algorithm of bias estimation with the conventionally used empirical method. As available forecast data sets are not large enough for a comprehensive test, synthetically generated time series representing the analysis (truth and forecast are used to increase the sample size. Since these synthetic time series retained the statistical characteristics of the observations and operational NWP model output, the results of this study can be extended to real observation and forecasts and this is confirmed by a preliminary test with real data.
By using the climatological mean and standard deviation of the meteorological variable in consideration and the statistical relationship between the forecast and the analysis, the Bayesian bias estimator outperforms the empirical approach in terms of the accuracy of the estimated bias, and it can reduce the required size of the training sample by a factor of 3. This advantage of the Bayesian approach is due to the fact that it is less liable to the sampling error in consecutive sampling. These results suggest that a carefully designed statistical procedure may reduce the need for the costly generation of large hindcast datasets.
Eddington-Malmquist bias in a cosmological context
Teerikorpi, P.
2015-01-01
In 1914, Eddington derived a formula for the difference between the mean absolute magnitudes of stars "in space" or gathered "from the sky". Malmquist (1920) derived a general relation for this difference in Euclidean space. Here we study this statistical bias in cosmology, clarifying and expanding previous work. We derived the Malmquist relation within a general cosmological framework, including Friedmann's model, analogously to the way Malmquist showed in 1936 that his formula is also valid...
Information environment, behavioral biases, and home bias in analysts’ recommendations
DEFF Research Database (Denmark)
Farooq, Omar; Taouss, Mohammed
2012-01-01
show that optimism difference between the two groups is more than twice as much in firms with poor information environment than in firms with better information environment. We argue that poor information environment pose greater information asymmetries to foreign analysts regarding local firms...... relative to local analysts. As a result, we expect them to be less optimistic in their recommendations relative to local analysts. However, for firms with better information environment, foreign analysts face less information asymmetries. As a result, they are relatively more optimistic (less pessimistic......Can information environment of a firm explain home bias in analysts’ recommendations? Can the extent of agency problems explain optimism difference between foreign and local analysts? This paper answers these questions by documenting the effect of information environment on home bias in analysts...
Statistical analysis of angular correlation measurements
International Nuclear Information System (INIS)
Obtaining the multipole mixing ratio, δ, of γ transitions in angular correlation measurements is a statistical problem characterized by the small number of angles in which the observation is made and by the limited statistic of counting, α. The inexistence of a sufficient statistics for the estimator of δ, is shown. Three different estimators for δ were constructed and their properties of consistency, bias and efficiency were tested. Tests were also performed in experimental results obtained in γ-γ directional correlation measurements. (Author)
Risk of bias versus quality assessment of randomised controlled trials: cross sectional study
Ospina, Maria; Liang, Yuanyuan; Dryden, Donna M; Hooton, Nicola; Krebs Seida, Jennifer; Klassen, Terry P
2009-01-01
Objectives To evaluate the risk of bias tool, introduced by the Cochrane Collaboration for assessing the internal validity of randomised trials, for inter-rater agreement, concurrent validity compared with the Jadad scale and Schulz approach to allocation concealment, and the relation between risk of bias and effect estimates. Design Cross sectional study. Study sample 163 trials in children. Main outcome measures Inter-rater agreement between reviewers assessing trials using the risk of bias tool (weighted κ), time to apply the risk of bias tool compared with other approaches to quality assessment (paired t test), degree of correlation for overall risk compared with overall quality scores (Kendall’s τ statistic), and magnitude of effect estimates for studies classified as being at high, unclear, or low risk of bias (metaregression). Results Inter-rater agreement on individual domains of the risk of bias tool ranged from slight (κ=0.13) to substantial (κ=0.74). The mean time to complete the risk of bias tool was significantly longer than for the Jadad scale and Schulz approach, individually or combined (8.8 minutes (SD 2.2) per study v 2.0 (SD 0.8), P<0.001). There was low correlation between risk of bias overall compared with the Jadad scores (P=0.395) and Schulz approach (P=0.064). Effect sizes differed between studies assessed as being at high or unclear risk of bias (0.52) compared with those at low risk (0.23). Conclusions Inter-rater agreement varied across domains of the risk of bias tool. Generally, agreement was poorer for those items that required more judgment. There was low correlation between assessments of overall risk of bias and two common approaches to quality assessment: the Jadad scale and Schulz approach to allocation concealment. Overall risk of bias as assessed by the risk of bias tool differentiated effect estimates, with more conservative estimates for studies at low risk. PMID:19841007
Opinion Dynamics with Confirmation Bias
Allahverdyan, A E
2014-01-01
Background: Confirmation bias is the tendency to acquire or evaluate new information in a way that is consistent with one's preexisting beliefs. It is omnipresent in psychology, economics, and even scientific practices. Prior theoretical research of this phenomenon has mainly focused on its economic implications possibly missing its potential connections with broader notions of cognitive science. Methodology/Principal Findings: We formulate a (non-Bayesian) model for revising subjective probabilistic opinion of a confirmationally-biased agent in the light of a persuasive opinion. The revision rule ensures that the agent does not react to persuasion that is either far from his current opinion or coincides with it. We demonstrate that the model accounts for the basic phenomenology of the social judgment theory, and allows to study various phenomena such as cognitive dissonance and boomerang effect. The model also displays the order of presentation effect|when consecutively exposed to two opinions, the preferenc...
International Nuclear Information System (INIS)
The origin of the exchange bias phenomenon is investigated on the basis of a quantum mechanical model. In particular, the mechanisms that determine the magnetic structure in the vicinity of an antiferromagnetic-ferromagnetic interface are reexamined. This way we establish how the breaking of translational invariance modifies quantum spin fluctuations. It is found that non-uniform fluctuations induce uncompensated spins in the antiferromagnet, which in turn give rise to a dipole field that couples to the magnetization of the ferromagnet. This coupling yields an exchange bias field that is of the order of magnitude of the one observed experimentally. A net surface magnetization should also be experimentally observable in a clean antiferromagnetic surface
International Nuclear Information System (INIS)
Alice is a charismatic quantum cryptographer who believes her parties are unmissable; Bob is a (relatively) glamorous string theorist who believes he is an indispensable guest. To prevent possibly traumatic collisions of self-perception and reality, their social code requires that decisions about invitation or acceptance be made via a cryptographically secure variable-bias coin toss (VBCT). This generates a shared random bit by the toss of a coin whose bias is secretly chosen, within a stipulated range, by one of the parties; the other party learns only the random bit. Thus one party can secretly influence the outcome, while both can save face by blaming any negative decisions on bad luck. We describe here some cryptographic VBCT protocols whose security is guaranteed by quantum theory and the impossibility of superluminal signaling, setting our results in the context of a general discussion of secure two-party computation. We also briefly discuss other cryptographic applications of VBCT
Cosmological Evolution of Linear Bias
Basilakos, S; Basilakos, Spyros; Plionis, Manolis
2000-01-01
Using linear perturbation theory and the Friedmann-Lemaitre solutions of the cosmological field equations, we derive analytically a second-order differential equation for the evolution of the linear bias factor, b(z), between the background matter and a mass-tracer fluctuation field. We find b(z) to be a strongly dependent function of redshift in all cosmological models. Comparing our analytical solution with the semi-analytic model of Mo & White, which utilises the Press-Schechter formalism and the gravitationally induced evolution of clustering, we find an extremely good agreement even at large redshifts, once we normalize to the same bias value at two different epochs, one of which is the present. Furthermore, our analytic b(z) function agrees well with the outcome of N-body simulations even up to large redshifts.
Probability biases as Bayesian inference
Directory of Open Access Journals (Sweden)
Andre; C. R. Martins
2006-11-01
Full Text Available In this article, I will show how several observed biases in human probabilistic reasoning can be partially explained as good heuristics for making inferences in an environment where probabilities have uncertainties associated to them. Previous results show that the weight functions and the observed violations of coalescing and stochastic dominance can be understood from a Bayesian point of view. We will review those results and see that Bayesian methods should also be used as part of the explanation behind other known biases. That means that, although the observed errors are still errors under the be understood as adaptations to the solution of real life problems. Heuristics that allow fast evaluations and mimic a Bayesian inference would be an evolutionary advantage, since they would give us an efficient way of making decisions. %XX In that sense, it should be no surprise that humans reason with % probability as it has been observed.
International Nuclear Information System (INIS)
Discussion was made on a phenomenological evidence to support the hypothesis that several new phenomena observed in low psub(t) physics are due to the presence of low-x QCD jets in minimum bias physics. The phenomena we examine are KNO scaling violations, growth of with multiplicity and rise of the non-single diffractive part of the total cross-section. We have discussed the importance of low-x hard parton scattering in minimum bias events and pointed out its connection to both KNO scaling violations as well as to the observed growth of with multiplicity in inclusive pion distributions. The contribution of these mini-jets to the total cross-section has been calculated and a model for the transverse energy distribution characterizing any event accompanied by jets has been presented. (author)
Chowdhry, D P
1995-01-01
This article identifies gender bias against female children and youth in India. Gender bias is based on centuries-old religious beliefs and sayings from ancient times. Discrimination is reflected in denial or ignorance of female children's educational, health, nutrition, and recreational needs. Female infanticide and selective abortion of female fetuses are other forms of discrimination. The task of eliminating or reducing gender bias will involve legal, developmental, political, and administrative measures. Public awareness needs to be created. There is a need to reorient the education and health systems and to advocate for gender equality. The government of India set the following goals for the 1990s: to protect the survival of the girl child and practice safe motherhood; to develop the girl child in general; and to protect vulnerable girl children in different circumstances and in special groups. The Health Authorities should monitor the laws carefully to assure marriage after the minimum age, ban sex determination of the fetus, and monitor the health and nutrition of pre-school girls and nursing and pregnant mothers. Mothers need to be encouraged to breast feed, and to breast feed equally between genders. Every village and slum area needs a mini health center. Maternal mortality must decline. Primary health centers and hospitals need more women's wards. Education must be universally accessible. Enrollments should be increased by educating rural tribal and slum parents, reducing distances between home and school, making curriculum more relevant to girls, creating more female teachers, and providing facilities and incentives for meeting the needs of girl students. Supplementary income could be provided to families for sending girls to school. Recreational activities must be free of gender bias. Dowry, sati, and devdasi systems should be banned. PMID:12158019
Investigating Endogeneity Bias in Marketing
Qing Liu; Thomas Otter; Greg M. Allenby
2007-01-01
The use of adaptive designs in conjoint analysis has been shown to lead to an endogeneity bias in part-worth estimates using sampling experiments. In this paper, we re-examine the endogeneity issue in light of the likelihood principle. The likelihood principle asserts that all relevant information in the data about model parameters is contained in the likelihood function. We show that, once the data are collected, adhering to the likelihood principle leads to analysis where endogeneity become...
Competition and Commercial Media Bias
BLASCO, A.; F. Sobbrio
2011-01-01
This paper reviews the empirical evidence on commercial media bias (i.e., advertisers influence over media accuracy) and then introduces a simple model to summarize the main elements of the theoretical literature. The analysis provides three main policy insights for media regulators: i) Media regulators should target their monitoring efforts towards news contents upon which advertisers are likely to share similar preferences; ii) In advertising industries characterized by high correlation in ...
Opinion Dynamics with Confirmation Bias
Allahverdyan, Armen E.; Aram Galstyan
2014-01-01
Background: Confirmation bias is the tendency to acquire or evaluate new information in a way that is consistent with one's preexisting beliefs. It is omnipresent in psychology, economics, and even scientific practices. Prior theoretical research of this phenomenon has mainly focused on its economic implications possibly missing its potential connections with broader notions of cognitive science. Methodology/Principal Findings: We formulate a (non-Bayesian) model for revising subjective proba...
Significant biases affecting abundance determinations
Wesson, Roger
2015-08-01
I have developed two highly efficient codes to automate analyses of emission line nebulae. The tools place particular emphasis on the propagation of uncertainties. The first tool, ALFA, uses a genetic algorithm to rapidly optimise the parameters of gaussian fits to line profiles. It can fit emission line spectra of arbitrary resolution, wavelength range and depth, with no user input at all. It is well suited to highly multiplexed spectroscopy such as that now being carried out with instruments such as MUSE at the VLT. The second tool, NEAT, carries out a full analysis of emission line fluxes, robustly propagating uncertainties using a Monte Carlo technique.Using these tools, I have found that considerable biases can be introduced into abundance determinations if the uncertainty distribution of emission lines is not well characterised. For weak lines, normally distributed uncertainties are generally assumed, though it is incorrect to do so, and significant biases can result. I discuss observational evidence of these biases. The two new codes contain routines to correctly characterise the probability distributions, giving more reliable results in analyses of emission line nebulae.
Automated statistical modeling of analytical measurement systems
International Nuclear Information System (INIS)
The statistical modeling of analytical measurement systems at the Idaho Chemical Processing Plant (ICPP) has been completely automated through computer software. The statistical modeling of analytical measurement systems is one part of a complete quality control program used by the Remote Analytical Laboratory (RAL) at the ICPP. The quality control program is an integration of automated data input, measurement system calibration, database management, and statistical process control. The quality control program and statistical modeling program meet the guidelines set forth by the American Society for Testing Materials and American National Standards Institute. A statistical model is a set of mathematical equations describing any systematic bias inherent in a measurement system and the precision of a measurement system. A statistical model is developed from data generated from the analysis of control standards. Control standards are samples which are made up at precise known levels by an independent laboratory and submitted to the RAL. The RAL analysts who process control standards do not know the values of those control standards. The object behind statistical modeling is to describe real process samples in terms of their bias and precision and, to verify that a measurement system is operating satisfactorily. The processing of control standards gives us this ability
Cosmetic Plastic Surgery Statistics
2014 Cosmetic Plastic Surgery Statistics Cosmetic Procedure Trends 2014 Plastic Surgery Statistics Report Please credit the AMERICAN SOCIETY OF PLASTIC SURGEONS when citing statistical data or using ...
Bias in Absolute Magnitude Determination from Parallaxes
Feast, Michael
2002-01-01
Relations are given for the correction of bias when mean absolute magnitudes are derived by the method of reduced parallaxes. The bias in the case of the derivation of the absolute magnitudes of individual objects is also considered.
On Infinite Quon Statistics and "Ambiguous" Statistics
Meljanac, S.; Milekovic, M.; Ristic, R.
1999-01-01
We critically examine a recent suggestion that "ambiguous" statistics is equivalent to infinite quon statistics and that it describes a dilute, nonrelativistics ideal gas of extremal black holes. We show that these two types of statistics are different and that the description of extremal black holes in terms of "ambiguous" statistics cannot be applied.
Selection bias and the perils of benchmarking.
Denrell, Jerker
2005-04-01
To find the secrets of business success, what could be more natural than studying successful businesses? In fact, nothing could be more dangerous, warns this Stanford professor. Generalizing from the examples of successful companies is like generalizing about New England weather from data taken only in the summer. That's essentially what businesspeople do when they learn from good examples and what consultants, authors, and researchers do when they study only existing companies or--worse yet--only high-performing companies. They reach conclusions from unrepresentative data samples, falling into the classic statistical trap of selection bias. Drawing on a wealth of case studies, for instance, one researcher concluded that great leaders share two key traits: They persist, often despite initial failures, and they are able to persuade others to join them. But those traits are also the hallmarks of spectacularly unsuccessful entrepreneurs, who must persist in the face of failure to incur large losses and must be able to persuade others to pour their money down the drain. To discover what makes a business successful, then, managers should look at both successes and failures. Otherwise, they will overvalue risky business practices, seeing only those companies that won big and not the ones that lost dismally. They will not be able to tell if their current good fortune stems from smart business practices or if they are actually coasting on past accomplishments or good luck. Fortunately, economists have developed relatively simple tools that can correct for selection bias even when data about failed companies are hard to come by. Success may be inspirational, but managers are more likely to find the secrets of high performance if they give the stories of their competitors'failures as full a hearing as they do the stories of dazzling successes. PMID:15807044
Quantifying selective reporting and the Proteus phenomenon for multiple datasets with similar bias.
Directory of Open Access Journals (Sweden)
Thomas Pfeiffer
Full Text Available Meta-analyses play an important role in synthesizing evidence from diverse studies and datasets that address similar questions. A major obstacle for meta-analyses arises from biases in reporting. In particular, it is speculated that findings which do not achieve formal statistical significance are less likely reported than statistically significant findings. Moreover, the patterns of bias can be complex and may also depend on the timing of the research results and their relationship with previously published work. In this paper, we present an approach that is specifically designed to analyze large-scale datasets on published results. Such datasets are currently emerging in diverse research fields, particularly in molecular medicine. We use our approach to investigate a dataset on Alzheimer's disease (AD that covers 1167 results from case-control studies on 102 genetic markers. We observe that initial studies on a genetic marker tend to be substantially more biased than subsequent replications. The chances for initial, statistically non-significant results to be published are estimated to be about 44% (95% CI, 32% to 63% relative to statistically significant results, while statistically non-significant replications have almost the same chance to be published as statistically significant replications (84%; 95% CI, 66% to 107%. Early replications tend to be biased against initial findings, an observation previously termed Proteus phenomenon: The chances for non-significant studies going in the same direction as the initial result are estimated to be lower than the chances for non-significant studies opposing the initial result (73%; 95% CI, 55% to 96%. Such dynamic patterns in bias are difficult to capture by conventional methods, where typically simple publication bias is assumed to operate. Our approach captures and corrects for complex dynamic patterns of bias, and thereby helps generating conclusions from published results that are more robust
Correcting power and p-value calculations for bias in diffusion tensor imaging.
Lauzon, Carolyn B; Landman, Bennett A
2013-07-01
Diffusion tensor imaging (DTI) provides quantitative parametric maps sensitive to tissue microarchitecture (e.g., fractional anisotropy, FA). These maps are estimated through computational processes and subject to random distortions including variance and bias. Traditional statistical procedures commonly used for study planning (including power analyses and p-value/alpha-rate thresholds) specifically model variability, but neglect potential impacts of bias. Herein, we quantitatively investigate the impacts of bias in DTI on hypothesis test properties (power and alpha-rate) using a two-sided hypothesis testing framework. We present theoretical evaluation of bias on hypothesis test properties, evaluate the bias estimation technique SIMEX for DTI hypothesis testing using simulated data, and evaluate the impacts of bias on spatially varying power and alpha rates in an empirical study of 21 subjects. Bias is shown to inflame alpha rates, distort the power curve, and cause significant power loss even in empirical settings where the expected difference in bias between groups is zero. These adverse effects can be attenuated by properly accounting for bias in the calculation of power and p-values. PMID:23465764
A Pharmacological Primer of Biased Agonism
Andresen1, Bradley T.
2011-01-01
Biased agonism is one of the fastest growing topics in G protein-coupled receptor pharmacology; moreover, biased agonists are used in the clinic today: carvedilol (Coreg®) is a biased agonist of beta-adrenergic receptors. However, there is a general lack of understanding of biased agonism when compared to traditional pharmacological terminology. Therefore, this review is designed to provide a basic introduction to classical pharmacology as well as G protein-coupled receptor signal transductio...
Galaxy peculiar velocities and evolution-bias
Percival, Will; Schafer, B.
2007-01-01
Galaxy bias can be split into two components: a formation-bias based on the locations of galaxy creation, and an evolution-bias that details their subsequent evolution. In this letter we consider evolution-bias in the peaks model. In this model, galaxy formation takes place at local maxima in the density field, and we analyse the subsequent peculiar motion of these galaxies in a linear model of structure formation. The peak restriction yields differences in the velocity distribution and corre...
Unlearning Implicit Social Biases During Sleep **
Hu, Xiaoqing; Antony, James W.; Creery, Jessica D.; Vargas, Iliana M.; Bodenhausen, Galen V.; Paller, Ken A.
2015-01-01
Although people may endorse egalitarianism and tolerance, social biases can remain operative and drive harmful actions in an unconscious manner. Here we investigated training to reduce implicit racial and gender bias. Forty participants processed counter-stereotype information paired with one sound for each type of bias. Biases were reduced immediately after training. During subsequent slow-wave sleep, one sound was unobtrusively presented to each participant, repeatedly, to reactivate one ty...
Selection bias in rheumatic disease research
Choi, Hyon K.; Nguyen, Uyen-Sa; Niu, Jingbo; Danaei, Goodarz; Zhang, Yuqing
2014-01-01
The identification of modifiable risk factors for the development of rheumatic conditions and their sequelae is crucial for reducing the substantial worldwide burden of these diseases. However, the validity of such research can be threatened by sources of bias, including confounding, measurement and selection biases. In this Review, we discuss potentially major issues of selection bias—a type of bias frequently overshadowed by other bias and feasibility issues, despite being equally or more p...
Spallation neutron source RF cavity bias system
International Nuclear Information System (INIS)
The Spallation Neutron Source r.f. cavity bias system is described under the topic headings: bias system, r.f. cavity, cables, d.c. bias power supply, transistor regulator and control system. Calculation of 4 core 300 mm solid aluminium cable inductance, coaxial shunt frequency response and transistor regulator computed frequency response, are discussed in appendices 1-3. (U.K.)
Begging the Question: Is Critical Thinking Biased?
Alston, Kal
1995-01-01
Discusses whether critical thinking is biased, examining what is meant by critical thinking and bias and what the consequences are for addressing bias in different ways. The paper responds to the three previous papers in the critical thinking symposium in this issue of the journal. (SM)
Outcome-Reporting Bias in Education Research
Pigott, Therese D.; Valentine, Jeffrey C.; Polanin, Joshua R.; Williams, Ryan T.; Canada, Dericka D.
2013-01-01
Outcome-reporting bias occurs when primary studies do not include information about all outcomes measured in a study. When studies omit findings on important measures, efforts to synthesize the research using systematic review techniques will be biased and interpretations of individual studies will be incomplete. Outcome-reporting bias has been…
DiPonio, Joseph M.
2010-01-01
The primary object of this study was to determine whether racial and/or gender bias were evidenced in the use of the ICIS-Principal. Specifically, will the use of the ICIS-Principal result in biased scores at a statistically significant level when rating current practicing administrators of varying gender and race. The study involved simulated…
Introducing Decorated HODs: modeling assembly bias in the galaxy-halo connection
Hearin, Andrew P; Bosch, Frank C van den; Campbell, Duncan; Tollerud, Erik
2015-01-01
The connection between galaxies and dark matter halos is often inferred from data using probabilistic models, such as the Halo Occupation Distribution (HOD). Conventional HOD formulations assume that only halo mass governs the galaxy-halo connection. Violations of this assumption, known as galaxy assembly bias, threaten the HOD program. We introduce decorated HODs, a new, flexible class of models designed to account for assembly bias. Decorated HODs minimally expand the parameter space and maximize the independence between traditional and novel HOD parameters. We use decorated HODs to quantify the influence of assembly bias on clustering and lensing statistics. For SDSS-like samples, the impact of assembly bias on galaxy clustering can be as large as a factor of two on r ~ 200 kpc scales and ~15% in the linear regime. Assembly bias can either enhance or diminish clustering on large scales, but generally increases clustering on scales r <~ 1 Mpc. We performed our calculations with Halotools, an open-source,...
MODIS/Terra 8-Day Clear Sky Radiance Bias Daily L3 Global 1Deg Zonal Bands V005
National Aeronautics and Space Administration — MODIS 8-day clear-sky radiance bias (observed - calculated) statistics are provided for 1Deg latitudinal zones and selected thermal bands. Separation by day and...
MODIS/Terra 8-Day Clear Sky Radiance Bias Daily L3 Global 1Deg Zonal Bands V006
National Aeronautics and Space Administration — MODIS 8-day clear-sky radiance bias (observed - calculated) statistics are provided for 1Deg latitudinal zones and selected thermal bands. Separation by day and...
MODIS/Aqua 8-Day Clear Sky Radiance Bias Daily L3 Global 1Deg Zonal Bands V005
National Aeronautics and Space Administration — MODIS 8-day clear-sky radiance bias (observed - calculated) statistics are provided for 1Deg latitudinal zones and selected thermal bands. Separation by day and...
MODIS/Aqua 8-Day Clear Sky Radiance Bias Daily L3 Global 1Deg Zonal Bands V006
National Aeronautics and Space Administration — MODIS 8-day clear-sky radiance bias (observed - calculated) statistics are provided for 1Deg latitudinal zones and selected thermal bands. Separation by day and...
A Review of Studies on Media Bias at Home
Institute of Scientific and Technical Information of China (English)
辛一丹
2015-01-01
Bias is widely existed nowadays.Domestic scholars have done a lot of research on the bias,especially the media bias.They studied the media bias from different perspectives,such as the bias on China image,the bias of a certain media FOX,the bias on the venerable group,the bias on women and so on.The author plans to give a review of the studies on media bias at home in this paper.
A Review of Studies on Media Bias at Home
Institute of Scientific and Technical Information of China (English)
辛一丹
2015-01-01
Bias is widely existed nowadays. Domestic scholars have done a lot of research on the bias, especially the media bias. They studied the media bias from different perspectives, such as the bias on China image,the bias of a certain media FOX, the bias on the venerable group, the bias on women and so on. The author plans to give a review of the studies on media bias at home in this paper.
Hindsight bias and investment decisions making empirical evidence form an emerging financial market
Muntazir Hussain; Syed Zulifiqar Ali Shah; Khalid Latif; Usman Bashir; Muhammad Yasir
2013-01-01
We studied the hindsight bias and investor decision making by employing the novel approach asset selection effect and sign of return effect. The study investigated the hindsight bias and investor decision making through questionnaires. The respondents are divided into three groups namely bank financial managers, stock market investors and students. The statistical significance of the asset selection effect and sign of return effect is tested by proportional z-test. Furthermore, the correlatio...
Koyama, Toshiyuki; Yamaji, Atsushi; Sato, Katsushi
2012-01-01
Linear structures perpendicular to an outcrop surface are easily discovered, but those parallel to the surface are not, giving rise to a biased orientation distribution of the structures. Here, we propose a bias correction method: Statistical inversion was conducted to unbias the distribution of the axes of mesoscale slump folds in the Cretaceous Izumi Group, Japan using the orientation distribution of outcrop surfaces. The observed axes showed a cluster in the SE quadrant. Their unbiased dis...
The Evolution of Rotation Group Bias: Will the Real Unemployment Rate Please Stand Up?
Alan B. Krueger; Mas, Alexandre; Niu, Xiaotong
2014-01-01
This paper documents that rotation group bias -- the tendency for labor force statistics to vary systematically by month in sample in labor force surveys -- in the Current Population Survey (CPS) has worsened considerably over time. The estimated unemployment rate for earlier rotation groups has grown sharply relative to the unemployment rate for later rotation groups; both should be nationally representative samples. The rise in rotation group bias is driven by a growing tendency for respond...
Diagnosing southeast tropical Atlantic SST and ocean circulation biases in the CMIP5 ensemble
Xu, Zhao; Chang, Ping; Richter, Ingo; Kim, Who; Tang, Guanglin
2014-12-01
Warm sea-surface temperature (SST) biases in the southeastern tropical Atlantic (SETA), which is defined by a region from 5°E to the west coast of southern Africa and from 10°S to 30°S, are a common problem in many current and previous generation climate models. The Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble provides a useful framework to tackle the complex issues concerning causes of the SST bias. In this study, we tested a number of previously proposed mechanisms responsible for the SETA SST bias and found the following results. First, the multi-model ensemble mean shows a positive shortwave radiation bias of ~20 W m-2, consistent with models' deficiency in simulating low-level clouds. This shortwave radiation error, however, is overwhelmed by larger errors in the simulated surface turbulent heat and longwave radiation fluxes, resulting in excessive heat loss from the ocean. The result holds for atmosphere-only model simulations from the same multi-model ensemble, where the effect of SST biases on surface heat fluxes is removed, and is not sensitive to whether the analysis region is chosen to coincide with the maximum warm SST bias along the coast or with the main SETA stratocumulus deck away from the coast. This combined with the fact that there is no statistically significant relationship between simulated SST biases and surface heat flux biases among CMIP5 models suggests that the shortwave radiation bias caused by poorly simulated low-level clouds is not the leading cause of the warm SST bias. Second, the majority of CMIP5 models underestimate upwelling strength along the Benguela coast, which is linked to the unrealistically weak alongshore wind stress simulated by the models. However, a correlation analysis between the model simulated vertical velocities and SST biases does not reveal a statistically significant relationship between the two, suggesting that the deficient coastal upwelling in the models is not simply related to the
Separate Universe Consistency Relation and Calibration of Halo Bias
Li, Yin; Takada, Masahiro
2015-01-01
Linear halo bias is the response of dark matter halo number density to a long wavelength fluctuation in the dark matter density. Using abundance matching between separate universe simulations which absorb the latter into a change in the background, we test the consistency relation between the change in a one point function, the halo mass function, and a two point function, the halo-matter cross correlation in the long wavelength limit. We find excellent agreement between the two at the $1-2\\%$ level for average halo biases between $1 \\lesssim \\bar b_1 \\lesssim 4$ and no statistically significant deviations at the $4-5\\%$ level out to $\\bar b_1 \\approx 8$. The separate universe technique provides a way of calibrating linear halo bias efficiently for even highly biased rare halos in the $\\Lambda$CDM model. Observational violation of the consistency relation would indicate new physics, e.g.~in the dark matter, dark energy or primordial non-Gaussianity sectors.
Stealth Bias in Gravitational-Wave Parameter Estimation
Vallisneri, Michele
2013-01-01
Inspiraling binaries of compact objects are primary targets for current and future gravitational-wave observatories. Waveforms computed in General Relativity are used to search for these sources, and will probably be used to extract source parameters from detected signals. However, if a different theory of gravity happens to be correct in the strong-field regime, source-parameter estimation may be affected by a fundamental bias: that is, by systematic errors induced due to the use of waveforms derived in the incorrect theory. If the deviations from General Relativity are not large enough to be detectable on their own and yet these systematic errors remain significant (i.e., larger than the statistical uncertainties in parameter estimation), fundamental bias cannot be corrected in a single observation, and becomes stealth bias. In this article we develop a scheme to determine in which cases stealth bias could be present in gravitational-wave astronomy. For a given observation, the answer depends on the detecti...
Analysis of the theoretical bias in dark matter direct detection
International Nuclear Information System (INIS)
Fitting the model ''A'' to dark matter direct detection data, when the model that underlies the data is ''B'', introduces a theoretical bias in the fit. We perform a quantitative study of the theoretical bias in dark matter direct detection, with a focus on assumptions regarding the dark matter interactions, and velocity distribution. We address this problem within the effective theory of isoscalar dark matter-nucleon interactions mediated by a heavy spin-1 or spin-0 particle. We analyze 24 benchmark points in the parameter space of the theory, using frequentist and Bayesian statistical methods. First, we simulate the data of future direct detection experiments assuming a momentum/velocity dependent dark matter-nucleon interaction, and an anisotropic dark matter velocity distribution. Then, we fit a constant scattering cross section, and an isotropic Maxwell-Boltzmann velocity distribution to the simulated data, thereby introducing a bias in the analysis. The best fit values of the dark matter particle mass differ from their benchmark values up to 2 standard deviations. The best fit values of the dark matter-nucleon coupling constant differ from their benchmark values up to several standard deviations. We conclude that common assumptions in dark matter direct detection are a source of potentially significant bias
A Biased Review of Sociophysics
Stauffer, Dietrich
2012-01-01
Various aspects of recent sociophysics research are shortly reviewed: Schelling model as an example for lack of interdisciplinary cooperation, opinion dynamics, combat, and citation statistics as an example for strong interdisciplinarity.
A Biased Review of Sociophysics
Stauffer, Dietrich
2013-04-01
Various aspects of recent sociophysics research are shortly reviewed: Schelling model as an example for lack of interdisciplinary cooperation, opinion dynamics, combat, and citation statistics as an example for strong interdisciplinarity.
Domain-size-dependent exchange bias in Co/LaFeO3
Energy Technology Data Exchange (ETDEWEB)
Scholl, A.; Nolting, F.; Seo, J.W.; Ohldag, H.; Stohr, J.; Raoux,S.; Locquet, J.-P.; Fompeyrine, J.
2004-09-22
X-ray microscopy using magnetic linear dichroism of a zero-field-grown, multi-domain Co/LaFeO{sub 3} ferromagnet/antiferromagnet sample shows a local exchange bias of random direction and magnitude. A statistical analysis of the local bias of individual, micron-size magnetic domains demonstrates an increasing bias field with decreasing domain size as expected for a random distribution of pinned, uncompensated spins, which are believed to mediate the interface coupling. A linear dependence with the inverse domain diameter is found.
Leyrat, C; Caille, A; Donner, A; Giraudeau, B
2013-08-30
Cluster randomized trials (CRTs) are often prone to selection bias despite randomization. Using a simulation study, we investigated the use of propensity score (PS) based methods in estimating treatment effects in CRTs with selection bias when the outcome is quantitative. Of four PS-based methods (adjustment on PS, inverse weighting, stratification, and optimal full matching method), three successfully corrected the bias, as did an approach using classical multivariable regression. However, they showed poorer statistical efficiency than classical methods, with higher standard error for the treatment effect, and type I error much smaller than the 5% nominal level. PMID:23553813
Unlearning Implicit Social Biases During Sleep **
Hu, Xiaoqing; Antony, James W.; Creery, Jessica D.; Vargas, Iliana M.; Bodenhausen, Galen V.; Paller, Ken A.
2015-01-01
Although people may endorse egalitarianism and tolerance, social biases can remain operative and drive harmful actions in an unconscious manner. Here we investigated training to reduce implicit racial and gender bias. Forty participants processed counter-stereotype information paired with one sound for each type of bias. Biases were reduced immediately after training. During subsequent slow-wave sleep, one sound was unobtrusively presented to each participant, repeatedly, to reactivate one type of training. Corresponding bias reductions were fortified in comparison to the social bias not externally reactivated during sleep. This advantage remained one week later, the magnitude of which was associated with time in slow-wave and rapid-eye-movement sleep after training. We conclude that memory reactivation during sleep enhances counter-stereotype training, and that maintaining a bias reduction is sleep-dependent. PMID:26023137
Distraction from emotional information reduces biased judgements.
Lench, Heather C; Bench, Shane W; Davis, Elizabeth L
2016-06-01
Biases arising from emotional processes are some of the most robust behavioural effects in the social sciences. The goal of this investigation was to examine the extent to which the emotion regulation strategy of distraction could reduce biases in judgement known to result from emotional information. Study 1 explored lay views regarding whether distraction is an effective strategy to improve decision-making and revealed that participants did not endorse this strategy. Studies 2-5 focused on several established, robust biases that result from emotional information: loss aversion, desirability bias, risk aversion and optimistic bias. Participants were prompted to divert attention away from their feelings while making judgements, and in each study this distraction strategy resulted in reduced bias in judgement relative to control conditions. The findings provide evidence that distraction can improve choice across several situations that typically elicit robustly biased responses, even though participants are not aware of the effectiveness of this strategy. PMID:25787937
Weak Lensing Peak Finding: Estimators, Filters, and Biases
Schmidt, Fabian
2010-01-01
Large catalogs of shear-selected peaks have recently become a reality. In order to properly interpret the abundance and properties of these peaks, it is necessary to take into account the effects of the clustering of source galaxies, among themselves and with the lens. In addition, the preferred selection of lensed galaxies in a flux- and size-limited sample leads to fluctuations in the apparent source density which correlate with the lensing field (lensing bias). In this paper, we investigate these issues for two different choices of shear estimators which are commonly in use today: globally-normalized and locally-normalized estimators. While in principle equivalent, in practice these estimators respond differently to systematic effects such as lensing bias and cluster member dilution. Furthermore, we find that which estimator is statistically superior depends on the specific shape of the filter employed for peak finding; suboptimal choices of the estimator+filter combination can result in a suppression of t...
The Bias in Bayes and How to Measure it
Directory of Open Access Journals (Sweden)
D.A. S. Fraser
2012-07-01
Full Text Available A Bayes prior with a likelihood can give approximate confidence and provide a remarkably flexible approach to statistical inference; but is also known to provide inaccurate perhaps incorrect results. We develop a measure of Bayes bias, first examining a simple Normal model and then progressing to quite general models with scalar and vector parameters. The Bias measure can be interpreted as the lateral displacement of the location standardized likelihood function and thus provides ready access to the effect of a prior on p-values, confidence bounds, and Bayes posterior bounds. The needed computation is comparable to that for the likelihood function and thus provides an initial option for checking merits of Bayesian computation for high dimensions.
Non-local bias contribution to third-order galaxy correlations
Bel, Julien; Gaztañaga, Enrique
2015-01-01
We study halo clustering bias with second- and third-order statistics of halo and matter density fields in the MICE Grand Challenge simulation. We verify that two-point correlations deliver reliable estimates of the linear bias parameters at large scales, while estimations from the variance can be significantly affected by non-linear and possibly non-local contributions to the bias function. Combining three-point auto- and cross-correlations we find, for the first time in configuration space, evidence for the presence of such non-local contributions. These contributions are consistent with predicted second-order non-local effects on the bias functions originating from the dark matter tidal field. Samples of massive haloes show indications of bias (local or non-local) beyond second order. Ignoring non-local bias causes $20-30$\\% and $5-10$\\% overestimation of the linear bias from three-point auto- and cross-correlations respectively. We study two third-order bias estimators which are not affected by second-ord...
Hindsight bias and investment decisions making empirical evidence form an emerging financial market
Directory of Open Access Journals (Sweden)
Muntazir Hussain
2013-05-01
Full Text Available We studied the hindsight bias and investor decision making by employing the novel approach asset selection effect and sign of return effect. The study investigated the hindsight bias and investor decision making through questionnaires. The respondents are divided into three groups namely bank financial managers, stock market investors and students. The statistical significance of the asset selection effect and sign of return effect is tested by proportional z-test. Furthermore, the correlation of the memory error and recall error is also determined. The overall perceived error (hindsight bias relationship is checked with the confidence in recall and confidence in estimate. We found strong evidence of hindsight bias in all respondents groups and its worst consequence on investment decision making. The bank financial managers were found less exposed to hindsight bias in comparison to stock market investors in asset selection effect. However, in sign of return effect the financial managers were more hindsight biased than the stock market investors. The relationship of hindsight bias and confidence in recall and confidence in estimate also confirms that all the respondents were hindsight biased and more confident in their estimate and less confident in their recall. All the respondents claim that they knew the phenomenon all along are wrong in their estimate. The respondents were unable to learn from previous errors and unable to detect their errors in estimate and recall. This error in prediction leads the investor to bear the risk above their accepted level which is harmful to their wealth.
Evaluation of bias and variance in low-count OSEM list mode reconstruction
International Nuclear Information System (INIS)
Statistical algorithms have been widely used in PET image reconstruction. The maximum likelihood expectation maximization reconstruction has been shown to produce bias in applications where images are reconstructed from a relatively small number of counts. In this study, image bias and variability in low-count OSEM reconstruction are investigated on images reconstructed with MOLAR (motion-compensation OSEM list-mode algorithm for resolution-recovery reconstruction) platform. A human brain ([11C]AFM) and a NEMA phantom are used in the simulation and real experiments respectively, for the HRRT and Biograph mCT. Image reconstructions were repeated with different combinations of subsets and iterations. Regions of interest were defined on low-activity and high-activity regions to evaluate the bias and noise at matched effective iteration numbers (iterations × subsets). Minimal negative biases and no positive biases were found at moderate count levels and less than 5% negative bias was found using extremely low levels of counts (0.2 M NEC). At any given count level, other factors, such as subset numbers and frame-based scatter correction may introduce small biases (1–5%) in the reconstructed images. The observed bias was substantially lower than that reported in the literature, perhaps due to the use of point spread function and/or other implementation methods in MOLAR. (paper)
Selection bias in rheumatic disease research
Choi, Hyon K.; Nguyen, Uyen-Sa; Niu, Jingbo; Danaei, Goodarz; Zhang, Yuqing
2014-01-01
The identification of modifiable risk factors for the development of rheumatic conditions and their sequelae is crucial for reducing the substantial worldwide burden of these diseases. However, the validity of such research can be threatened by sources of bias, including confounding, measurement and selection biases. In this Review, we discuss potentially major issues of selection bias—a type of bias frequently overshadowed by other bias and feasibility issues, despite being equally or more problematic—in key areas of rheumatic disease research. We present index event bias (a type of selection bias) as one of the potentially unifying reasons behind some unexpected findings, such as the ‘risk factor paradox’—a phenomenon exemplified by the discrepant effects of certain risk factors on the development versus the progression of osteoarthritis (OA) or rheumatoid arthritis (RA). We also discuss potential selection biases owing to differential loss to follow-up in RA and OA research, as well as those due to the depletion of susceptibles (prevalent user bias) and immortal time bias. The lesson remains that selection bias can be ubiquitous and, therefore, has the potential to lead the field astray. Thus, we conclude with suggestions to help investigators avoid such issues and limit the impact on future rheumatology research. PMID:24686510
Value measurement in statistically uncertain conditions
Gorban, I. I.
2008-01-01
A mathematical model for measuring values has been proposed taking into account the uncertainty of statistical conditions of forming the measured value and its estimate. This model is based on presenting measured value and its estimate as hyper-random values. The point and interval methods of estimating hyper-random values have been developed. The notions of biased, consistent and efficient estimates were extended to the case of hyper-random estimates. The potential accuracy of measurements w...
Statistical Discrimination in a Competitive Labor Market
Jonathan B. Berk
1999-01-01
This paper studies the effect of employee job selection in a model of statistical discrimination in a competitive labor market. In an economy in which there are quality differences between groups, a surprisingly strong condition is required to guarantee discrimination against the worse qualified group --- MLRP must hold. In addition, because of the self-selection bias induced by competition, the resulting discrimination is small when compared to the magnitude of the underlying quality differe...
Forecasts: uncertain, inaccurate and biased?
DEFF Research Database (Denmark)
Nicolaisen, Morten Skou; Ambrasaite, Inga; Salling, Kim Bang
2012-01-01
construction costs, which account for the majority of total project costs. Second are the forecasts of travel time savings, which account for the majority of total project benefits. The latter of these is, inter alia, determined by forecasts of travel demand, which we shall use as a proxy for the forecasting......Cost Benefit Analysis (CBA) is the dominating methodology for appraisal of transport infrastructure projects across the globe. In order to adequately assess the costs and benefits of such projects two types of forecasts are crucial to the validity of the appraisal. First are the forecasts of...... accuracy of project benefits. This paper presents results from an on-going research project on uncertainties in transport project evaluation (UNITE) that find forecasts of demand to be not only uncertain, but at times also highly inaccurate and often displaying a concerning degree of bias. Demand for road...
Modeling confirmation bias and polarization
Del Vicario, Michela; Caldarelli, Guido; Stanley, H Eugene; Quattrociocchi, Walter
2016-01-01
Online users tend to select claims that adhere to their system of beliefs and to ignore dissenting information. Confirmation bias, indeed, plays a pivotal role in viral phenomena. Furthermore, the wide availability of content on the web fosters the aggregation of likeminded people where debates tend to enforce group polarization. Such a configuration might alter the public debate and thus the formation of the public opinion. In this paper we provide a mathematical model to study online social debates and the related polarization dynamics. We assume the basic updating rule of the Bounded Confidence Model (BCM) and we develop two variations a) the Rewire with Bounded Confidence Model (RBCM), in which discordant links are broken until convergence is reached; and b) the Unbounded Confidence Model, under which the interaction among discordant pairs of users is allowed even with a negative feedback, either with the rewiring step (RUCM) or without it (UCM). From numerical simulations we find that the new models (UCM...
Social reward shapes attentional biases.
Anderson, Brian A
2016-01-01
Paying attention to stimuli that predict a reward outcome is important for an organism to survive and thrive. When visual stimuli are associated with tangible, extrinsic rewards such as money or food, these stimuli acquire high attentional priority and come to automatically capture attention. In humans and other primates, however, many behaviors are not motivated directly by such extrinsic rewards, but rather by the social feedback that results from performing those behaviors. In the present study, I examine whether positive social feedback can similarly influence attentional bias. The results show that stimuli previously associated with a high probability of positive social feedback elicit value-driven attentional capture, much like stimuli associated with extrinsic rewards. Unlike with extrinsic rewards, however, such stimuli also influence task-specific motivation. My findings offer a potential mechanism by which social reward shapes the information that we prioritize when perceiving the world around us. PMID:25941868
Symmetry as Bias: Rediscovering Special Relativity
Lowry, Michael R.
1992-01-01
This paper describes a rational reconstruction of Einstein's discovery of special relativity, validated through an implementation: the Erlanger program. Einstein's discovery of special relativity revolutionized both the content of physics and the research strategy used by theoretical physicists. This research strategy entails a mutual bootstrapping process between a hypothesis space for biases, defined through different postulated symmetries of the universe, and a hypothesis space for physical theories. The invariance principle mutually constrains these two spaces. The invariance principle enables detecting when an evolving physical theory becomes inconsistent with its bias, and also when the biases for theories describing different phenomena are inconsistent. Structural properties of the invariance principle facilitate generating a new bias when an inconsistency is detected. After a new bias is generated. this principle facilitates reformulating the old, inconsistent theory by treating the latter as a limiting approximation. The structural properties of the invariance principle can be suitably generalized to other types of biases to enable primal-dual learning.
Quantum Criticality in the Biased Dicke Model.
Zhu, Hanjie; Zhang, Guofeng; Fan, Heng
2016-01-01
The biased Dicke model describes a system of biased two-level atoms coupled to a bosonic field, and is expected to produce new phenomena that are not present in the original Dicke model. In this paper, we study the critical properties of the biased Dicke model in the classical oscillator limits. For the finite-biased case in this limit, We present analytical results demonstrating that the excitation energy does not vanish for arbitrary coupling. This indicates that the second order phase transition is avoided in the biased Dicke model, which contrasts to the original Dicke model. We also analyze the squeezing and the entanglement in the ground state, and find that a finite bias will strongly modify their behaviors in the vicinity of the critical coupling point. PMID:26786239
Cognitive Biases and Nonverbal Cue Availability in Detecting Deception
Burgoon, Judee K.; Blair, J. Pete; Strom, Renee E.
2008-01-01
In potentially deceptive situations, people rely on mental shortcuts to help process information. These heuristic judgments are often biased and result in inaccurate assessments of sender veracity. Four such biases--truth bias, visual bias, demeanor bias, and expectancy violation bias--were examined in a judgment experiment that varied nonverbal…
Savage, Leonard J
1972-01-01
Classic analysis of the foundations of statistics and development of personal probability, one of the greatest controversies in modern statistical thought. Revised edition. Calculus, probability, statistics, and Boolean algebra are recommended.
... Shop With CureSearch Blog Donate Now Select Page Childhood Cancer Statistics Home > Understanding Children’s Cancer > Childhood Cancer Statistics Childhood Cancer Statistics – Graphs and Infographics Number of Diagnoses ...
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... Tumor > Neuroendocrine Tumor - Statistics Request Permissions Neuroendocrine Tumor - Statistics Approved by the Cancer.Net Editorial Board , 04/ ... the body. It is important to remember that statistics on how many people survive this type of ...
... Cost Global More Prevalence Disability Suicide Cost Global Statistics Understanding the scope of mental illnesses and their ... those affected receive treatment. The information on these statistics pages includes the best statistics currently available on ...
Publication Bias in Methodological Computational Research
Anne-Laure Boulesteix; Veronika Stierle; Alexander Hapfelmeier
2015-01-01
The problem of publication bias has long been discussed in research fields such as medicine. There is a consensus that publication bias is a reality and that solutions should be found to reduce it. In methodological computational research, including cancer informatics, publication bias may also be at work. The publication of negative research findings is certainly also a relevant issue, but has attracted very little attention to date. The present paper aims at providing a new formal framework...
Investigating bias in squared regression structure coefficients
Nimon, Kim F.; Zientek, Linda R.; Thompson, Bruce
2015-01-01
The importance of structure coefficients and analogs of regression weights for analysis within the general linear model (GLM) has been well-documented. The purpose of this study was to investigate bias in squared structure coefficients in the context of multiple regression and to determine if a formula that had been shown to correct for bias in squared Pearson correlation coefficients and coefficients of determination could be used to correct for bias in squared regression structure coefficie...
Exponential Growth Bias and Financial Literacy
Almenberg, Johan; Gerdes, Christer
2011-01-01
The tendency to underestimate the future value of a variable growing at a constant rate, an example of exponential growth bias, has been linked to household financial decision making. We show that exponential growth bias and standard measures of financial literacy are negatively correlated in a representative sample of Swedish adults. Since financial literacy is linked to household decision making, our results indicate that examining the relationship between exponential growth bias and househ...
Voter Confirmation Bias and Electoral Accountability
Lockwood, Benjamin
2015-01-01
This paper considers the implications of an important cognitive bias in information processing, confirmation bias, in a political agency setting. In the baseline two-period case where only the politician’s actions are observable before the election, we show that when voters have this bias, it decreases pandering by the incumbent, and can raise voter welfare as a consequence. This result is robust in several directions, including to the case where the voter can also observe payoffs with some p...
BUSINESS LEADERSHIP BIASES: ANDROCENTRISM, ETHNOCENTRISM AND CHRONOCENTRISM
SOFICA Aurelian; NEGRUTA Adina
2012-01-01
The aim of the paper is to explore the unconscious biases that accompany the business leadership icons. The main objectives of the paper are: to look for evidence of leadership biases on ground of gender (androcentrism), ethnicity (ethnocentrism) and age (cronocentrism); to look for potential reasons behind the biases and for potential effects at the organizational and social level. The article confirms some of the evidence from various international empirical or theoretical studies, and prop...
Childhood Obesity: Issues of Weight Bias
Washington, Reginald L.
2011-01-01
Although the effects of obesity on children's physical health are well documented, the social consequences of obesity are less well described and may not be addressed in intervention programs. Weight bias may take several forms. It may result in teasing and discrimination and may affect employment and educational opportunities. Health care providers may limit care of overweight or obese children. The media promote weight bias in multiple ways. Some parents are biased against their obese child...
δ-biased Josephson tunnel junctions
International Nuclear Information System (INIS)
The behavior of a long Josephson tunnel junction drastically depends on the distribution of the dc bias current. We investigate the case in which the bias current is fed in the central point of a one-dimensional junction. Such junction configuration has been recently used to detect the persistent currents circulating in a superconducting loop. Analytical and numerical results indicate that the presence of fractional vortices leads to remarkable differences from the conventional case of uniformly distributed dc bias current. The theoretical findings are supported by detailed measurements on a number of δ-biased samples having different electrical and geometrical parameters.
Weak coin flipping with small bias
Kerenidis, I; Kerenidis, Iordanis; Nayak, Ashwin
2002-01-01
This note presents a quantum protocol that demonstrates that_weak_ coin flipping with bias approximately 0.239, less than 1/4, is possible. A bias of 1/4 was the smallest known, and followed from the strong coin flipping protocol of [Ambainis 2001]. Protocols with yet smaller bias, approximately 0.207, have independently been discovered [Ambainis 2001, Spekkens and Rudolph 2002]. We also present an alternative strong coin flipping protocol with bias 1/4 with analysis simpler than that of [Ambainis 2001].
Bias-correction in vector autoregressive models
DEFF Research Database (Denmark)
Engsted, Tom; Pedersen, Thomas Quistgaard
2014-01-01
We analyze the properties of various methods for bias-correcting parameter estimates in both stationary and non-stationary vector autoregressive models. First, we show that two analytical bias formulas from the existing literature are in fact identical. Next, based on a detailed simulation study...... improvement over ordinary least squares. We pay special attention to the risk of pushing an otherwise stationary model into the non-stationary region of the parameter space when correcting for bias. Finally, we consider a recently proposed reduced-bias weighted least squares estimator, and we find that it...
Memory biased random walk approach to synthetic clickstream generation
Antulov-Fantulin, Nino; Zlatic, Vinko; Grcar, Miha; Smuc, Tomislav
2012-01-01
Personalized recommender systems rely on personal usage data of each user in the system. However, privacy policies protecting users' rights prevent this data of being publicly available to a wider researcher audience. In this work, we propose a memory biased random walk model (MBRW) based on real clickstream graphs, as a generator of synthetic clickstreams that conform to statistical properties of the real clickstream data, while, at the same time, adhering to the privacy protection policies. We show that synthetic clickstreams can be used to learn recommender system models which achieve high recommender performance on real data and at the same time assuring that strong de-minimization guarantees are provided.
Algebraic statistics computational commutative algebra in statistics
Pistone, Giovanni; Wynn, Henry P
2000-01-01
Written by pioneers in this exciting new field, Algebraic Statistics introduces the application of polynomial algebra to experimental design, discrete probability, and statistics. It begins with an introduction to Gröbner bases and a thorough description of their applications to experimental design. A special chapter covers the binary case with new application to coherent systems in reliability and two level factorial designs. The work paves the way, in the last two chapters, for the application of computer algebra to discrete probability and statistical modelling through the important concept of an algebraic statistical model.As the first book on the subject, Algebraic Statistics presents many opportunities for spin-off research and applications and should become a landmark work welcomed by both the statistical community and its relatives in mathematics and computer science.
Economic Statistics or Statistical Methods in Economics?
Directory of Open Access Journals (Sweden)
Richard Hindls
2014-12-01
Full Text Available In teaching statistics to economists, it often happens that insuffi cient distinction is drawn between statistical methods applied on economic data on the one hand, and economic statistics as a special discipline with its own theoretic basis, fundamental notions and a specific concept of indices on the other hand. The authors endeavour to point out pitfalls of this insuffi cient distinction and introduce didactic ways to resolve this problem.
Official statistical publications and economic statistics
Mavis Anagboso; Allan Flowers; Geoff Tily; Gavin Wallis
2007-01-01
Introduces the new journal and provides a retrospective review of compendia publications of official statistics and analysis.Since its first publication in 1953, Economic Trends and its companion labour market publications have recordedchanges to the UK economy and labour market. In this new publication, Economic & Labour Market Review,the Office for National Statistics brings these two fields of economic statistics into a single publication. As patterns ofeconomic activity and work change, t...
Effect of percent non-detects on estimation bias in censored distributions
Zhang, Z.; Lennox, W. C.; Panu, U. S.
2004-09-01
Uniqueness of the problem surrounding non-detects has been a concern alike to researchers and statisticians dealing with summary statistics while analyzing censored data. To incorporate non-detects in the estimation process, a simple substitution by the MDL (method detection limit) and the maximum likelihood estimation method are routinely implemented as standard methods by US-EPA laboratories. In situations where numerical standards are set at or near the MDL by regulatory agencies, it is prudent and important to closely investigate both the variability in test measurements and the estimation bias, because an inference based on biased estimates could entail significant liabilities. Variability is understood to be not only inevitable but also an inherent and integral part of any chemical analysis or test. In situations where regulatory agencies fail to account for the inherently present variability of test measurements, there is a need for regulated facilities to seek remedial action merely as a consequence of inadequate statistical procedure. This paper utilizes a mathematical approach to derive the bias functions and resulting bias curves are developed to investigate the censored samples from a variety of probability distributions such as normal, log-normal, gamma, and Gumbel distributions. Finally, the bias functions and bias curves are also compared to the results obtained by using Monte Carlo simulations.
System Model Bias Processing Approach for Regional Coordinated States Information Involved Filtering
Directory of Open Access Journals (Sweden)
Zebo Zhou
2016-01-01
Full Text Available In the Kalman filtering applications, the conventional dynamic model which connects the states information of two consecutive epochs by state transition matrix is usually predefined and assumed to be invariant. Aiming to improve the adaptability and accuracy of dynamic model, we propose multiple historical states involved filtering algorithm. An autoregressive model is used as the dynamic model which is subsequently combined with observation model for deriving the optimal window-recursive filter formulae in the sense of minimum mean square error principle. The corresponding test statistics characteristics of system residuals are discussed in details. The test statistics of regional predicted residuals are then constructed in a time-window for model bias testing with two hypotheses, that is, the null and alternative hypotheses. Based on the innovations test statistics, we develop a model bias processing procedure including bias detection, location identification, and state correction. Finally, the minimum detectable bias and bias-to-noise ratio are both computed for evaluating the internal and external reliability of overall system, respectively.
Jak, S.; Oort, F.J.; Dolan, C. V.
2010-01-01
Restricted factor analysis can be used to investigate measurement bias. A prerequisite for the detection of measurement bias through factor analysis is the correct specification of the measurement model. We applied restricted factor analysis to two subtests of a Dutch cognitive ability test. These two examples serve to illustrate the relationship between multidimensionality and measurement bias. We conclude that measurement bias implies multidimensionality, whereas multidimensionality shows u...
Distinctive Characteristics of Sexual Orientation Bias Crimes
Stacey, Michele
2011-01-01
Despite increased attention in the area of hate crime research in the past 20 years, sexual orientation bias crimes have rarely been singled out for study. When these types of crimes are looked at, the studies are typically descriptive in nature. This article seeks to increase our knowledge of sexual orientation bias by answering the question:…
delta-biased Josephson tunnel junctions
DEFF Research Database (Denmark)
Monaco, R.; Mygind, Jesper; Koshelet, V.;
2010-01-01
Abstract: The behavior of a long Josephson tunnel junction drastically depends on the distribution of the dc bias current. We investigate the case in which the bias current is fed in the central point of a one-dimensional junction. Such junction configuration has been recently used to detect the...
Production bias and cluster annihilation: Why necessary?
DEFF Research Database (Denmark)
Singh, B.N.; Trinkaus, H.; Woo, C.H.
1994-01-01
the primary cluster density is high. Therefore, a sustained high swelling rate driven by production bias must involve the annihilation of primary clusters at sinks. A number of experimental observations which are unexplainable in terms of the conventional dislocation bias for monointerstitials is...
A simple model for biased divertors
Energy Technology Data Exchange (ETDEWEB)
Lachambre, J.-L.; Quirion, B.; Gunn, J.; Boucher, C.; Stansfield, B.; Gauvreau, J.-L. [Centre canadien de fusion magnetique, 1804, boulevard Lionel-Boulet, Varennes, Quebec, J3X 1S1 (Canada)
1997-12-01
Ionization near the target plate is shown to play an important role in biasing experiments. Our previous SOL model, which calculates the induced radial electric field, is found to be inadequate to treat the new divertor geometry of TdeV. When recycling is included via the measured D{sub {alpha}} emission near the plate, the upgraded model correctly reproduces all the observed electric currents and fields during biasing in the new divertor configuration. A simple divertor model using this calculated field has been developed to simulate the evolution of the divertor ion and neutral parameters under the action of neutralization plate biasing. Using a 1D adiabatic fluid model for the divertor ions, a 1D convective representation for the SOL neutrals and a 0D calculation for the plenum pressure, this divertor model satisfactorily simulates most of the TdeV biasing experiments at all biasing voltages and all toroidal field directions at low line-averaged densities. The weaker agreement at high densities is largely a consequence of the crudeness of the general divertor physics rather than of the deficiency of the biasing physics implemented in the model. The model is finally used to explain the polarity asymmetries observed in divertor efficiencies during biasing, and to demonstrate that no mechanism other than plate current saturation is required to interpret the saturation of toroidal rotation observed in the SOL at large biasing voltages of either polarity. (author)
Understanding Implicit Bias: What Educators Should Know
Staats, Cheryl
2016-01-01
The desire to ensure the best for children is precisely why educators should become aware of the concept of implicit bias: the attitudes or stereotypes that affect our understanding, actions, and decisions in an unconscious manner. Operating outside of our conscious awareness, implicit biases are pervasive, and they can challenge even the most…
Biases in Children's and Adults' Moral Judgments
Powell, Nina L.; Derbyshire, Stuart W. G.; Guttentag, Robert E.
2012-01-01
Two experiments examined biases in children's (5/6- and 7/8-year-olds) and adults' moral judgments. Participants at all ages judged that it was worse to produce harm when harm occurred (a) through action rather than inaction (omission bias), (b) when physical contact with the victim was involved (physical contact principle), and (c) when the harm…
Racially Biased Policing: Determinants of Citizen Perceptions
Weitzer, Ronald; Tuch, Steven A.
2005-01-01
The current controversy surrounding racial profiling in America has focused renewed attention on the larger issue of racial bias by the police. Yet little is known about the extent of police racial bias and even less about public perceptions of the problem. This article analyzes recent national survey data on citizens' views of and reported…
How Many Hindsight Biases Are There?
Blank, Hartmut; Nestler, Steffen; von Collani, Gernot; Fischer, Volkhard
2008-01-01
The answer is three: questioning a conceptual default assumption in hindsight bias research, we argue that the hindsight bias is not a unitary phenomenon but consists of three separable and partially independent subphenomena or components, namely, memory distortions, impressions of foreseeability and impressions of necessity. Following a detailed…
Attention bias modification: the Emperor's new suit?
Directory of Open Access Journals (Sweden)
Emmelkamp Paul MG
2012-06-01
Full Text Available Abstract A series of primarily laboratory-based studies found attention bias modification in socially anxious participants to lead to reduced anxiety. It is argued that the failure to replicate the positive results of attention bias modification in the study of Carlbring et al. may be due to reasons other than the application through the Internet. A number of controlled studies failed to replicate the positive effects of attention bias modification in clinically rather than subclinically socially anxious subjects. Given the lack of robust evidence for attention bias modification in clinically socially anxious individuals, the author is inclined to consider attention bias modification as 'the Emperor's new suit'. Results achieved with regular Internet-based treatments for social anxiety disorder based on cognitive therapy and exposure methods are much better than those achieved with attention bias modification procedures delivered 'face to face' in clinically distressed participants. Given the lack of robust evidence for attention bias modification in clinical samples, there is no need yet to investigate the implementation of attention bias modification through the Internet. Please see related article: http://www.biomedcentral.com/1471-244X/12/66
EVIDENCE OF NATIONALISTIC BIAS IN MUAYTHAI
Directory of Open Access Journals (Sweden)
Tony D. Myers
2006-07-01
Full Text Available MuayThai is a combat sport with a growing international profile but limited research conducted into judging practices and processes. Problems with judging of other subjectively judged combat sports have caused controversy at major international tournaments that have resulted in changes to scoring methods. Nationalistic bias has been central to these problems and has been identified across a range of sports. The aim of this study was to examine nationalistic bias in MuayThai. Data were collected from the International Federation of MuayThai Amateur (IFMA World Championships held in Almaty, Kazakhstan September 2003 and comprised of tournament results from 70 A-class MuayThai bouts each judged by between five and nine judges. Bouts examined featured 62 competitors from 21 countries and 25 judges from 11 countries. Results suggested that nationalistic bias was evident. The bias observed equated to approximately one round difference between opposing judges over the course of a bout (a mean of 1.09 (SE=0.50 points difference between judges with opposing affilations. The number of neutral judges used meant that this level of bias generally did not influence the outcome of bouts. Future research should explore other ingroup biases, such as nearest neighbour bias and political bias as well as investigating the feasibility adopting an electronic scoring system
Estimating Sampling Selection Bias in Human Genetics: A Phenomenological Approach
Risso, Davide; Taglioli, Luca; De Iasio, Sergio; Gueresi, Paola; Alfani, Guido; Nelli, Sergio; Rossi, Paolo; Paoli, Giorgio; Tofanelli, Sergio
2015-01-01
This research is the first empirical attempt to calculate the various components of the hidden bias associated with the sampling strategies routinely-used in human genetics, with special reference to surname-based strategies. We reconstructed surname distributions of 26 Italian communities with different demographic features across the last six centuries (years 1447–2001). The degree of overlapping between "reference founding core" distributions and the distributions obtained from sampling the present day communities by probabilistic and selective methods was quantified under different conditions and models. When taking into account only one individual per surname (low kinship model), the average discrepancy was 59.5%, with a peak of 84% by random sampling. When multiple individuals per surname were considered (high kinship model), the discrepancy decreased by 8–30% at the cost of a larger variance. Criteria aimed at maximizing locally-spread patrilineages and long-term residency appeared to be affected by recent gene flows much more than expected. Selection of the more frequent family names following low kinship criteria proved to be a suitable approach only for historically stable communities. In any other case true random sampling, despite its high variance, did not return more biased estimates than other selective methods. Our results indicate that the sampling of individuals bearing historically documented surnames (founders' method) should be applied, especially when studying the male-specific genome, to prevent an over-stratification of ancient and recent genetic components that heavily biases inferences and statistics. PMID:26452043
Purohit, Sudha G; Deshmukh, Shailaja R
2015-01-01
STATISTICS USING R will be useful at different levels, from an undergraduate course in statistics, through graduate courses in biological sciences, engineering, management and so on. The book introduces statistical terminology and defines it for the benefit of a novice. For a practicing statistician, it will serve as a guide to R language for statistical analysis. For a researcher, it is a dual guide, simultaneously explaining appropriate statistical methods for the problems at hand and indicating how these methods can be implemented using the R language. For a software developer, it is a guide in a variety of statistical methods for development of a suite of statistical procedures.
Expressing precision and bias in calorimetry
Energy Technology Data Exchange (ETDEWEB)
Hauck, Danielle K [Los Alamos National Laboratory; Croft, Stephen [Los Alamos National Laboratory; Bracken, David S [Los Alamos National Laboratory
2010-01-01
The calibration and calibration verification of a nuclear calorimeter represents a substantial investment of time in part because a single calorimeter measurement takes of the order of 2 to 24h to complete. The time to complete a measurement generally increases with the size of the calorimeter measurement well. It is therefore important to plan the sequence of measurements rather carefully so as to cover the dynamic range and achieve the required accuracy within a reasonable time frame. This work will discuss how calibrations and their verification has been done in the past and what we consider to be good general practice in this regard. A proposed approach to calibration and calibration verification is presented which, in the final analysis, makes use of all the available data - both calibration and verification collectively - in order to obtain the best (in a best fit sense) possible calibration. The combination of sample variance and percent recovery are traditionally taken as sufficient to capture the random (precision) and systematic (bias) contributions to the uncertainty in a calorimetric assay. These terms have been defined as well as formulated for a basic calibration. It has been tradition to assume that sensitivity is a linear function of power. However, the availability of computer power and statistical packages should be utilized to fit the response function as accurately as possible using whatever functions are deemed most suitable. Allowing for more flexibility in the response function fit will enable the calibration to be updated according to the results from regular validation measurements through the year. In a companion paper to be published elsewhere we plan to discuss alternative fitting functions.
Variance bias analysis for the Gelbard's batch method
International Nuclear Information System (INIS)
In this paper, variances and the bias will be derived analytically when the Gelbard's batch method is applied. And then, the real variance estimated from this bias will be compared with the real variance calculated from replicas. Variance and the bias were derived analytically when the batch method was applied. If the batch method was applied to calculate the sample variance, covariance terms between tallies which exist in the batch were eliminated from the bias. With the 2 by 2 fission matrix problem, we could calculate real variance regardless of whether or not the batch method was applied. However as batch size got larger, standard deviation of real variance was increased. When we perform a Monte Carlo estimation, we could get a sample variance as the statistical uncertainty of it. However, this value is smaller than the real variance of it because a sample variance is biased. To reduce this bias, Gelbard devised the method which is called the Gelbard's batch method. It has been certificated that a sample variance get closer to the real variance when the batch method is applied. In other words, the bias get reduced. This fact is well known to everyone in the MC field. However, so far, no one has given the analytical interpretation on it
Galaxy Bias in Quintessence Cosmological Models
Basilakos, S
2003-01-01
We derive the evolution of the linear bias factor, $b(z)$, in cosmological models driven by an exotic fluid with an equation of state: $p_{x}=w\\rho_{x}$, where $-1\\le w<0$ (quintessence). Our aim is to put constrains on different cosmological and biasing models by combining the recent observational clustering results of optical ({\\em 2dF}) galaxies (Hawkings et al.) with those predicted by the models. We find that our bias model when fitted to the {\\em 2dF} clustering results predicts different bias evolution for different values of $w$. The models that provide the weak biasing ($b_{\\circ} \\sim 1.1$) of optical galaxies found in many recent observational studies are flat, $\\Omega_{\\rm m}=0.3$ with $w\\le -0.9$. These models however, predict a weak redshift evolution of $b(z)$, not corroborated by N-body simulations.
Composite biasing in Monte Carlo radiative transfer
Baes, Maarten; Lunttila, Tuomas; Bianchi, Simone; Camps, Peter; Juvela, Mika; Kuiper, Rolf
2016-01-01
Biasing or importance sampling is a powerful technique in Monte Carlo radiative transfer, and can be applied in different forms to increase the accuracy and efficiency of simulations. One of the drawbacks of the use of biasing is the potential introduction of large weight factors. We discuss a general strategy, composite biasing, to suppress the appearance of large weight factors. We use this composite biasing approach for two different problems faced by current state-of-the-art Monte Carlo radiative transfer codes: the generation of photon packages from multiple components, and the penetration of radiation through high optical depth barriers. In both cases, the implementation of the relevant algorithms is trivial and does not interfere with any other optimisation techniques. Through simple test models, we demonstrate the general applicability, accuracy and efficiency of the composite biasing approach. In particular, for the penetration of high optical depths, the gain in efficiency is spectacular for the spe...
Implicit Social Biases in People With Autism.
Birmingham, Elina; Stanley, Damian; Nair, Remya; Adolphs, Ralph
2015-11-01
Implicit social biases are ubiquitous and are known to influence social behavior. A core diagnostic criterion of autism spectrum disorders (ASD) is abnormal social behavior. We investigated the extent to which individuals with ASD might show a specific attenuation of implicit social biases, using Implicit Association Tests (IATs) involving social (gender, race) and nonsocial (nature, shoes) categories. High-functioning adults with ASD showed intact but reduced IAT effects relative to healthy control participants. We observed no selective attenuation of implicit social (vs. nonsocial) biases in our ASD population. To extend these results, we supplemented our healthy control data with data collected from a large online sample from the general population and explored correlations between autistic traits and IAT effects. We observed no systematic relationship between autistic traits and implicit social biases in our online and control samples. Taken together, these results suggest that implicit social biases, as measured by the IAT, are largely intact in ASD. PMID:26386014
Racial Bias in the Juvenile Justice System in the United States.
Pratt, Menah A. E.
1993-01-01
Examines research on racial bias, focusing on the discretionary decision-making junctures of the juvenile court system. Research and statistics continue to suggest that the public, the police, the prosecution, and the jury all treat blacks more unfairly based to a large extent on race. (SLD)
DEFF Research Database (Denmark)
Dossing, Anna; Tarp, Simon; Furst, Daniel E;
2014-01-01
INTRODUCTION: When participants drop out of randomised clinical trials, as frequently happens, the intention-to-treat (ITT) principle does not apply, potentially leading to attrition bias. Data lost from patient dropout/lack of follow-up are statistically addressed by imputing, a procedure prone to...
Dopaminergic genes predict individual differences in susceptibility to confirmation bias.
Doll, Bradley B; Hutchison, Kent E; Frank, Michael J
2011-04-20
The striatum is critical for the incremental learning of values associated with behavioral actions. The prefrontal cortex (PFC) represents abstract rules and explicit contingencies to support rapid behavioral adaptation in the absence of cumulative experience. Here we test two alternative models of the interaction between these systems, and individual differences thereof, when human subjects are instructed with prior information about reward contingencies that may or may not be accurate. Behaviorally, subjects are overly influenced by prior instructions, at the expense of learning true reinforcement statistics. Computational analysis found that this pattern of data is best accounted for by a confirmation bias mechanism in which prior beliefs--putatively represented in PFC--influence the learning that occurs in the striatum such that reinforcement statistics are distorted. We assessed genetic variants affecting prefrontal and striatal dopaminergic neurotransmission. A polymorphism in the COMT gene (rs4680), associated with prefrontal dopaminergic function, was predictive of the degree to which participants persisted in responding in accordance with prior instructions even as evidence against their veracity accumulated. Polymorphisms in genes associated with striatal dopamine function (DARPP-32, rs907094, and DRD2, rs6277) were predictive of learning from positive and negative outcomes. Notably, these same variants were predictive of the degree to which such learning was overly inflated or neglected when outcomes are consistent or inconsistent with prior instructions. These findings indicate dissociable neurocomputational and genetic mechanisms by which initial biases are strengthened by experience. PMID:21508242
The ergodicity bias in the observed galaxy distribution
Energy Technology Data Exchange (ETDEWEB)
Pan, Jun [The Purple Mountain Observatory, 2 West Beijing Road, Nanjing 210008 (China); Zhang, Pengjie, E-mail: jpan@pmo.ac.cn, E-mail: pjzhang@shao.ac.cn [Key Laboratory for Research in Galaxies and Cosmology, Shanghai Astronomical Observatory, 80 Nandan Road, Shanghai, 200030 (China)
2010-08-01
The spatial distribution of galaxies we observed is subject to the given condition that we, human beings are sitting right in a galaxy — the Milky Way. Thus the ergodicity assumption is questionable in interpretation of the observed galaxy distribution. The resultant difference between observed statistics (volume average) and the true cosmic value (ensemble average) is termed as the ergodicity bias. We perform explicit numerical investigation of the effect for a set of galaxy survey depths and near-end distance cuts. It is found that the ergodicity bias in observed two- and three-point correlation functions in most cases is insignificant for modern analysis of samples from galaxy surveys and thus close a loophole in precision cosmology. However, it may become non-negligible in certain circumstances, such as those applications involving three-point correlation function at large scales of local galaxy samples. Thus one is reminded to take extra care in galaxy sample construction and interpretation of the statistics of the sample, especially when the characteristic redshift is low.
Natural auditory scene statistics shapes human spatial hearing.
Parise, Cesare V; Knorre, Katharina; Ernst, Marc O
2014-04-22
Human perception, cognition, and action are laced with seemingly arbitrary mappings. In particular, sound has a strong spatial connotation: Sounds are high and low, melodies rise and fall, and pitch systematically biases perceived sound elevation. The origins of such mappings are unknown. Are they the result of physiological constraints, do they reflect natural environmental statistics, or are they truly arbitrary? We recorded natural sounds from the environment, analyzed the elevation-dependent filtering of the outer ear, and measured frequency-dependent biases in human sound localization. We find that auditory scene statistics reveals a clear mapping between frequency and elevation. Perhaps more interestingly, this natural statistical mapping is tightly mirrored in both ear-filtering properties and in perceived sound location. This suggests that both sound localization behavior and ear anatomy are fine-tuned to the statistics of natural auditory scenes, likely providing the basis for the spatial connotation of human hearing. PMID:24711409
Rumsey, Deborah
2011-01-01
The fun and easy way to get down to business with statistics Stymied by statistics? No fear ? this friendly guide offers clear, practical explanations of statistical ideas, techniques, formulas, and calculations, with lots of examples that show you how these concepts apply to your everyday life. Statistics For Dummies shows you how to interpret and critique graphs and charts, determine the odds with probability, guesstimate with confidence using confidence intervals, set up and carry out a hypothesis test, compute statistical formulas, and more.Tracks to a typical first semester statistics cou
Industrial statistics with Minitab
Cintas, Pere Grima; Llabres, Xavier Tort-Martorell
2012-01-01
Industrial Statistics with MINITAB demonstrates the use of MINITAB as a tool for performing statistical analysis in an industrial context. This book covers introductory industrial statistics, exploring the most commonly used techniques alongside those that serve to give an overview of more complex issues. A plethora of examples in MINITAB are featured along with case studies for each of the statistical techniques presented. Industrial Statistics with MINITAB: Provides comprehensive coverage of user-friendly practical guidance to the essential statistical methods applied in industry.Explores
Forecast Bias Correction: A Second Order Method
Crowell, Sean
2010-01-01
The difference between a model forecast and actual observations is called forecast bias. This bias is due to either incomplete model assumptions and/or poorly known parameter values and initial/boundary conditions. In this paper we discuss a method for estimating corrections to parameters and initial conditions that would account for the forecast bias. A set of simple experiments with the logistic ordinary differential equation is performed using an iterative version of a first order version of our method to compare with the second order version of the method.
Skill-Biased Technological Change in Denmark
DEFF Research Database (Denmark)
Malchow-Møller, Nikolaj; Rose Skaksen, Jan
2003-01-01
Skill-Biased Technological Change in Denmark:A Disaggregate Perspective@*In this paper, we provide an industry-level analysis of skill-biased technological change(SBTC) in Denmark over the last two decades. The analysis shows that SBTC has variedconsiderably across industries, and traditionally l...... information aboutfuture labour requirements, as the relative importance of these industries must be expectedto grow, thereby reinforcing the shift in demand for skilled labour.JEL Classification: J24, J31, L6Keywords: skill-biased technological change, Danish industries...
Bias Correction Intercomparison Project (BCIP): an introduction and the first results
Nikulin, Grigory; Bosshard, Thomas; Yang, Wei; Bärring, Lars; Wilcke, Renate; Vrac, Mathieu; Vautard, Robert; Noel, Thomas; Gutiérrez, José Manuel; Herrera, Sixto; Fernández, Jesús; Haugen, Jan Erik; Benestad, Rasmus; Landgren, Oskar Andreas; Grillakis, Manolis; Ioannis, Tsanis; Koutroulis, Aristeidis; Dosio, Alessandro; Ferrone, Andrew; Switanek, Matthew
2015-04-01
There is a growing demand on regional climate change information for use in impact modelling which in turn provides downstream input for decision-making. Such information generated by climate models has a number of uncertainties and one of them is ability of climate models to accurately simulate the complex climate system. All model are only an approximation of the real climate system and have different errors or biases resulting in deviation of the simulated climate from the observed once. Nowadays, it is widely recognised that climate model results, as an input to impact models, cannot be used directly and an adjustment (bias correction) towards the observed climatology is necessary. Applying bias adjustment to climate model simulations introduces a new, unexplored level of uncertainty in impact modelling and often the bias-adjusted simulations are blindly used even if their limitations are very well known. To fill such bias-adjustment-related gaps in use of climate information a Bias Correction Intercomparison Project (BCIP) has been recently established. The BCIP addresses following topics: i) to quantify what level of uncertainties bias adjustment introduces to workflow of climate information, ii) to advance bias-adjustment technique and iii) to provide the best practice on use of the bias-adjusted climate simulations. Within the BCIP two experiments focusing on different climate zones have been designed, namely: one on the mid-latitude climate taking the Euro-CORDEX simulations (50km) and the E-OBS data set as a reference and the second on the tropical climate using the CORDEX-Africa simulations (50km) and the WATCH ERA-Interim data set as a reference. Applying different bias-correction methods and different modifications of the same method to the same input data sets allows assessing impact of bias-correction technique on climate simulations. A number of various statistics describing climatology are taken for evaluation and analysis starting from basic
DEFF Research Database (Denmark)
Lindström, Erik; Madsen, Henrik; Nielsen, Jan Nygaard
Statistics for Finance develops students’ professional skills in statistics with applications in finance. Developed from the authors’ courses at the Technical University of Denmark and Lund University, the text bridges the gap between classical, rigorous treatments of financial mathematics...
... About Blood > Blood Facts and Statistics Printable Version Blood Facts and Statistics Facts about blood needs Facts ... about American Red Cross Blood Services Facts about blood needs Every two seconds someone in the U.S. ...
Cancer Statistics: Pancreas Cancer
... qnad9A-rfcw?rel=0 SEER Stat Fact Sheets: Pancreas Cancer Expand All Collapse All Statistics at a ... 5 Years Or More after Being Diagnosed with Pancreas Cancer? Relative survival statistics compare the survival of ...
Recreational Boating Statistics 2012
Department of Homeland Security — Every year, the USCG compiles statistics on reported recreational boating accidents. These statistics are derived from accident reports that are filed by the owners...
... population data for older age groups are available. Statistics at a Glance Show More At a Glance ... with ovarian cancer in the United States. Survival Statistics Show More How Many People Survive 5 Years ...
... population data for older age groups are available. Statistics at a Glance Show More At a Glance ... living with leukemia in the United States. Survival Statistics Show More How Many People Survive 5 Years ...
U.S. Department of Health & Human Services — The CMS Office of Enterprise Data and Analytics has developed CMS Program Statistics, which includes detailed summary statistics on national health care, Medicare...
Overweight and Obesity Statistics
... the full list of resources . Overweight and Obesity Statistics Page Content About Overweight and Obesity Prevalence of ... adults age 20 and older [ Top ] Physical Activity Statistics Adults Research Findings Research suggests that staying active ...
... Research AMIGAS Fighting Cervical Cancer Worldwide Stay Informed Statistics for Other Kinds of Cancer Breast Cervical Colorectal ( ... Skin Vaginal and Vulvar Cancer Home Uterine Cancer Statistics Language: English Español (Spanish) Recommend on Facebook Tweet ...
Recreational Boating Statistics 2013
Department of Homeland Security — Every year, the USCG compiles statistics on reported recreational boating accidents. These statistics are derived from accident reports that are filed by the owners...
Recreational Boating Statistics 2011
Department of Homeland Security — Every year, the USCG compiles statistics on reported recreational boating accidents. These statistics are derived from accident reports that are filed by the owners...
Applying contemporary statistical techniques
Wilcox, Rand R
2003-01-01
Applying Contemporary Statistical Techniques explains why traditional statistical methods are often inadequate or outdated when applied to modern problems. Wilcox demonstrates how new and more powerful techniques address these problems far more effectively, making these modern robust methods understandable, practical, and easily accessible.* Assumes no previous training in statistics * Explains how and why modern statistical methods provide more accurate results than conventional methods* Covers the latest developments on multiple comparisons * Includes recent advanc
Strominger, Andrew
1993-01-01
The quantum statistics of charged, extremal black holes is investigated beginning with the hypothesis that the quantum state is a functional on the space of closed three-geometries, with each black hole connected to an oppositely charged black hole through a spatial wormhole. From this starting point a simple argument is given that a collection of extremal black holes obeys neither Bose nor Fermi statistics. Rather they obey an exotic variety of particle statistics known as ``infinite statist...
Valley Fever (Coccidioidomycosis) Statistics
... Candidiasis Oropharyngeal / Esophageal Candidiasis Genital / vulvovaginal candidiasis Invasive candidiasis Definition Symptoms Risk & Prevention Sources Diagnosis Treatment Statistics Healthcare Professionals ...
Mathematical statistics with applications
Ramachandran, KM
2009-01-01
Mathematical Statistics with Applications provides a calculus-based theoretical introduction to mathematical statistics while emphasizing interdisciplinary applications as well as exposure to modern statistical computational and simulation concepts that are not covered in other textbooks. Includes the Jackknife, Bootstrap methods, the EM algorithms and Markov chain Monte Carlo methods. Prior probability or statistics knowledge is not required.* Step-by-step procedure to solve real problems, making the topic more accessible* Exercises blend theory and modern applications*
Lenard, Christopher; McCarthy, Sally; Mills, Terence
2014-01-01
There are many different aspects of statistics. Statistics involves mathematics, computing, and applications to almost every field of endeavour. Each aspect provides an opportunity to spark someone's interest in the subject. In this paper we discuss some ethical aspects of statistics, and describe how an introduction to ethics has been…
A Bias in the Diagnosis of Schizophrenia
Reade, William Kent; Wertheimer, Michael
1976-01-01
Research shows a relationship between diagnoses of schizophrenia among twins. It was studied whether information that a twin was schizophrenic would bias diagnoses. Such information almost doubled the rater's estimates of probability of schizophrenia in a hypothetical case history. (NG)
Future research in weight bias: What next?
Alberga, Angela S; Russell-Mayhew, Shelly; von Ranson, Kristin M; McLaren, Lindsay; Ramos Salas, Ximena; Sharma, Arya M
2016-06-01
The 2015 Canadian Weight Bias Summit disseminated the newest research advances and brought together 40 experts, stakeholders, and policy makers in various disciplines in health, education, and public policy to identify future research directions in weight bias. In this paper we aim to share the results of the Summit as well as encourage international and interdisciplinary research collaborations in weight bias reduction. Consensus emerged on six research areas that warrant further investigation in weight bias: costs, causes, measurement, qualitative research and lived experience, interventions, and learning from other models of discrimination. These discussions highlighted three key lessons that were informed by the Summit, namely: language matters, the voices of people living with obesity should be incorporated, and interdisciplinary stakeholders should be included. PMID:27129601
Bootstrap bias-adjusted GMM estimators
Ramalho, Joaquim J.S.
2005-01-01
The ability of six alternative bootstrap methods to reduce the bias of GMM parameter estimates is examined in an instrumental variable framework using Monte Carlo analysis. Promising results were found for the two bootstrap estimators suggested in the paper.
Accounting for Unobservable Exposure Time Bias Wh...
U.S. Department of Health & Human Services — Accounting for Unobservable Exposure Time Bias When Using Medicare Prescription Drug Data Unobservable exposure time is common among Medicare Part D beneficiaries,...
Bias Modeling for Distantly Supervised Relation Extraction
Directory of Open Access Journals (Sweden)
Yang Xiang
2015-01-01
Full Text Available Distant supervision (DS automatically annotates free text with relation mentions from existing knowledge bases (KBs, providing a way to alleviate the problem of insufficient training data for relation extraction in natural language processing (NLP. However, the heuristic annotation process does not guarantee the correctness of the generated labels, promoting a hot research issue on how to efficiently make use of the noisy training data. In this paper, we model two types of biases to reduce noise: (1 bias-dist to model the relative distance between points (instances and classes (relation centers; (2 bias-reward to model the possibility of each heuristically generated label being incorrect. Based on the biases, we propose three noise tolerant models: MIML-dist, MIML-dist-classify, and MIML-reward, building on top of a state-of-the-art distantly supervised learning algorithm. Experimental evaluations compared with three landmark methods on the KBP dataset validate the effectiveness of the proposed methods.
Gaidos, Eric
2012-01-01
Statistical analyses of large surveys for transiting planets such as the Kepler mission must account for systematic errors and biases. Transit detection depends not only on the planet's radius and orbital period, but also on host star properties. Thus, a sample of stars with transiting planets may not accurately represent the target population. Moreover, targets are selected using criteria such as a limiting apparent magnitude. These selection effects, combined with uncertainties in stellar radius, lead to biases in the properties of transiting planets and their host stars. We quantify possible biases in the Kepler survey. First, Eddington bias produced by a steep planet radius distribution and uncertainties in stellar radius results in a 15-20% overestimate of planet occurrence. Second, the magnitude limit of the Kepler target catalog induces Malmquist bias towards large, more luminous stars and underestimation of the radii of about one third of candidate planets, especially those larger than Neptune. Third,...
Energy Biased Technical Change: A CGE Analysis
Löschel, Andreas; Otto, Vincent M.; Rob B. Dellink
2005-01-01
This paper studies energy bias in technical change. For this purpose, we develop a computable general equilibrium model that builds on endogenous growth models. The model explicitly captures links between energy, the rate and direction of technical change, and the economy. We derive the equilibrium determinants of biased technical change and show the importance of feedback in technical change, substitution possibilities between final goods, and general-equilibrium effects for the equilibrium ...
Constraints on Assembly Bias from Galaxy Clustering
Zentner, Andrew R.; Hearin, Andrew; Bosch, Frank C. van den; Lange, Johannes U.; Villarreal, Antonio
2016-01-01
We constrain the newly-introduced decorated Halo Occupation Distribution (HOD) model using SDSS DR7 measurements of projected galaxy clustering or r-band luminosity threshold samples. The decorated HOD is a model for the galaxy-halo connection that augments the HOD by allowing for the possibility of galaxy assembly bias: galaxy luminosity may be correlated with dark matter halo properties besides mass, Mvir. We demonstrate that it is not possible to rule out galaxy assembly bias using DR7 mea...
Spending Biased Legislators - Discipline Through Disagreement
Facundo Piguillem; Alessandro Riboni
2013-01-01
This paper studies politicians who have a present-bias for spending; they want to increase current spending and procrastinate spending cuts. We argue that legislators' bias is more severe in economies with low institutional quality. We show that disagreement in legislatures leads to policy persistence and that this attenuates the temptation to overspend. Depending on the environment, legislators' decisions to be fiscally responsible may either complement or substitute other legislator's decis...
Bias, Misinformation and the Paradox of Neutrality
Bednar, Peter; Welch, Christine
2008-01-01
What is normally described as bias? A possible definition comprises attempts to distort or mislead to achieve a certain perspective, i.e. subjective descriptions intended to mislead. If designers were able to exclude bias from informing systems, then this would maximize their effectiveness. This implicit conjecture appears to underpin much of the research in our field. However, in our efforts to support the evolution and design of informing systems, the way we think, communicate and conceptua...
Clustering coefficient without degree correlations biases
Soffer, Sara Nadiv; Vazquez, Alexei
2004-01-01
The clustering coefficient quantifies how well connected are the neighbors of a vertex in a graph. In real networks it decreases with the vertex degree, which has been taken as a signature of the network hierarchical structure. Here we show that this signature of hierarchical structure is a consequence of degree correlation biases in the clustering coefficient definition. We introduce a new definition in which the degree correlation biases are filtered out, and provide evidence that in real n...
The Local Bias of Individual Investors
Ning Zhu
2002-01-01
This study investigates individual investors' bias towards nearby companies. Using data from a large U.S. discount brokerage, we find that individual investors tend to invest in companies closer to them relative to the market portfolio. Unlike Coval and Moskowitz's (1999) findings on institutional investors, however, we find that advantageous information cannot explain individual investors' local bias. Accounting numbers and information asymmetry matter less to individual investors' local bia...
Biased liquid crystal photonic bandgap fiber
DEFF Research Database (Denmark)
Weirich, Johannes; Lægsgaard, Jesper; Alkeskjold, Thomas Tanggaard;
2008-01-01
We simulate the director structure of all capillaries in a biased photonic crystal fiber infiltrated with liquid crystals. Various mode simulations for different capillaries show the necessity to consider the entire structure.......We simulate the director structure of all capillaries in a biased photonic crystal fiber infiltrated with liquid crystals. Various mode simulations for different capillaries show the necessity to consider the entire structure....
Resolving Bias in Laser Ablation Geochronology
Bowring, James; Horstwood, Matthew; Gehrels, George
2013-06-01
Increasingly, scientific investigations requiring geochronology utilize laser ablation (LA)-inductively coupled plasma mass spectrometry (ICPMS), taking advantage of the efficiency and throughput possible for uranium-thorium-lead (U-Th-Pb) dating. A number of biases exist when comparing data among laboratories and an ongoing community-based effort is working to resolve and eliminate these biases to improve the accuracy of scientific interpretation based on these data.
Invited Commentary: Causal Diagrams and Measurement Bias
Hernán, Miguel A.; Cole, Stephen R.
2009-01-01
Causal inferences about the effect of an exposure on an outcome may be biased by errors in the measurement of either the exposure or the outcome. Measurement errors of exposure and outcome can be classified into 4 types: independent nondifferential, dependent nondifferential, independent differential, and dependent differential. Here the authors describe how causal diagrams can be used to represent these 4 types of measurement bias and discuss some problems that arise when using measured expo...
Local Bias and Stock Market Conditions
Giannetti, Mariassunta; Laeven, Luc
2012-01-01
We show that the local bias in U.S. mutual fund portfolios varies significantly over time and is more pronounced at times of heightened market uncertainty, such as during financial crises. Similarly, the local bias is less pronounced in periods when market sentiment is strong. These results do not depend on past fund performance or fund inflows during good times. Additionally, we do not find that fund managers earn superior returns on local stocks during periods of heightened market uncertain...
Time Series Properties of Expectation Biases
Kinari, Yusuke
2011-01-01
This study exammes time senes properties of expectation biases usmg a highfrequency survey on stock price forecasts, which required participants to forecast the Nikkei 225 over three forecasting horizons: one day, one week, and one month ahead. Constructing proxies for overconfidence and optimism as the expectation biases, this study shows that overconfidence is likely to remain stable over time while optimism is not. Moreover, a relationship exists between optimism and stock price movement, ...
Explorations in statistics: statistical facets of reproducibility.
Curran-Everett, Douglas
2016-06-01
Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This eleventh installment of Explorations in Statistics explores statistical facets of reproducibility. If we obtain an experimental result that is scientifically meaningful and statistically unusual, we would like to know that our result reflects a general biological phenomenon that another researcher could reproduce if (s)he repeated our experiment. But more often than not, we may learn this researcher cannot replicate our result. The National Institutes of Health and the Federation of American Societies for Experimental Biology have created training modules and outlined strategies to help improve the reproducibility of research. These particular approaches are necessary, but they are not sufficient. The principles of hypothesis testing and estimation are inherent to the notion of reproducibility in science. If we want to improve the reproducibility of our research, then we need to rethink how we apply fundamental concepts of statistics to our science. PMID:27231259
Constraints on Assembly Bias from Galaxy Clustering
Zentner, Andrew R; Bosch, Frank C van den; Lange, Johannes U; Villarreal, Antonio
2016-01-01
We constrain the newly-introduced decorated Halo Occupation Distribution (HOD) model using SDSS DR7 measurements of projected galaxy clustering or r-band luminosity threshold samples. The decorated HOD is a model for the galaxy-halo connection that augments the HOD by allowing for the possibility of galaxy assembly bias: galaxy luminosity may be correlated with dark matter halo properties besides mass, Mvir. We demonstrate that it is not possible to rule out galaxy assembly bias using DR7 measurements of galaxy clustering alone. Moreover, galaxy samples with Mr < -20 and Mr < -20.5 favor strong central galaxy assembly bias. These samples prefer scenarios in which high-concentration are more likely to host a central galaxy relative to low-concentration halos of the same mass. We exclude zero assembly bias with high significance for these samples. Satellite galaxy assembly bias is significant for the faintest sample, Mr < -19. We find no evidence for assembly bias in the Mr < -21 sample. Assembly bi...
Statistics Essentials For Dummies
Rumsey, Deborah
2010-01-01
Statistics Essentials For Dummies not only provides students enrolled in Statistics I with an excellent high-level overview of key concepts, but it also serves as a reference or refresher for students in upper-level statistics courses. Free of review and ramp-up material, Statistics Essentials For Dummies sticks to the point, with content focused on key course topics only. It provides discrete explanations of essential concepts taught in a typical first semester college-level statistics course, from odds and error margins to confidence intervals and conclusions. This guide is also a perfect re
Griffiths, Dawn
2009-01-01
Wouldn't it be great if there were a statistics book that made histograms, probability distributions, and chi square analysis more enjoyable than going to the dentist? Head First Statistics brings this typically dry subject to life, teaching you everything you want and need to know about statistics through engaging, interactive, and thought-provoking material, full of puzzles, stories, quizzes, visual aids, and real-world examples. Whether you're a student, a professional, or just curious about statistical analysis, Head First's brain-friendly formula helps you get a firm grasp of statistics
Statistics & probaility for dummies
Rumsey, Deborah J
2013-01-01
Two complete eBooks for one low price! Created and compiled by the publisher, this Statistics I and Statistics II bundle brings together two math titles in one, e-only bundle. With this special bundle, you'll get the complete text of the following two titles: Statistics For Dummies, 2nd Edition Statistics For Dummies shows you how to interpret and critique graphs and charts, determine the odds with probability, guesstimate with confidence using confidence intervals, set up and carry out a hypothesis test, compute statistical formulas, and more. Tra
Dowdy, Shirley; Chilko, Daniel
2011-01-01
Praise for the Second Edition "Statistics for Research has other fine qualities besides superior organization. The examples and the statistical methods are laid out with unusual clarity by the simple device of using special formats for each. The book was written with great care and is extremely user-friendly."-The UMAP Journal Although the goals and procedures of statistical research have changed little since the Second Edition of Statistics for Research was published, the almost universal availability of personal computers and statistical computing application packages have made it possible f
Business statistics for dummies
Anderson, Alan
2013-01-01
Score higher in your business statistics course? Easy. Business statistics is a common course for business majors and MBA candidates. It examines common data sets and the proper way to use such information when conducting research and producing informational reports such as profit and loss statements, customer satisfaction surveys, and peer comparisons. Business Statistics For Dummies tracks to a typical business statistics course offered at the undergraduate and graduate levels and provides clear, practical explanations of business statistical ideas, techniques, formulas, and calculations, w
Boslaugh, Sarah
2013-01-01
Need to learn statistics for your job? Want help passing a statistics course? Statistics in a Nutshell is a clear and concise introduction and reference for anyone new to the subject. Thoroughly revised and expanded, this edition helps you gain a solid understanding of statistics without the numbing complexity of many college texts. Each chapter presents easy-to-follow descriptions, along with graphics, formulas, solved examples, and hands-on exercises. If you want to perform common statistical analyses and learn a wide range of techniques without getting in over your head, this is your book.
Nonparametric statistical inference
Gibbons, Jean Dickinson
2010-01-01
Overall, this remains a very fine book suitable for a graduate-level course in nonparametric statistics. I recommend it for all people interested in learning the basic ideas of nonparametric statistical inference.-Eugenia Stoimenova, Journal of Applied Statistics, June 2012… one of the best books available for a graduate (or advanced undergraduate) text for a theory course on nonparametric statistics. … a very well-written and organized book on nonparametric statistics, especially useful and recommended for teachers and graduate students.-Biometrics, 67, September 2011This excellently presente
Estimation and inferential statistics
Sahu, Pradip Kumar; Das, Ajit Kumar
2015-01-01
This book focuses on the meaning of statistical inference and estimation. Statistical inference is concerned with the problems of estimation of population parameters and testing hypotheses. Primarily aimed at undergraduate and postgraduate students of statistics, the book is also useful to professionals and researchers in statistical, medical, social and other disciplines. It discusses current methodological techniques used in statistics and related interdisciplinary areas. Every concept is supported with relevant research examples to help readers to find the most suitable application. Statistical tools have been presented by using real-life examples, removing the “fear factor” usually associated with this complex subject. The book will help readers to discover diverse perspectives of statistical theory followed by relevant worked-out examples. Keeping in mind the needs of readers, as well as constantly changing scenarios, the material is presented in an easy-to-understand form.
Lectures on algebraic statistics
Drton, Mathias; Sullivant, Seth
2009-01-01
How does an algebraic geometer studying secant varieties further the understanding of hypothesis tests in statistics? Why would a statistician working on factor analysis raise open problems about determinantal varieties? Connections of this type are at the heart of the new field of "algebraic statistics". In this field, mathematicians and statisticians come together to solve statistical inference problems using concepts from algebraic geometry as well as related computational and combinatorial techniques. The goal of these lectures is to introduce newcomers from the different camps to algebraic statistics. The introduction will be centered around the following three observations: many important statistical models correspond to algebraic or semi-algebraic sets of parameters; the geometry of these parameter spaces determines the behaviour of widely used statistical inference procedures; computational algebraic geometry can be used to study parameter spaces and other features of statistical models.
Improved Arctic sea ice thickness projections using bias corrected CMIP5 simulations
Melia, N.; Haines, K.; Hawkins, E.
2015-07-01
Projections of Arctic sea ice thickness (SIT) have the potential to inform stakeholders about accessibility to the region, but are currently rather uncertain. The latest suite of CMIP5 Global Climate Models (GCMs) produce a wide range of simulated SIT in the historical period (1979-2014) and exhibit various spatial and temporal biases when compared with the Pan-Arctic Ice Ocean Modelling and Assimilation System (PIOMAS) sea ice reanalysis. We present a new method to constrain such GCM simulations of SIT to narrow projection uncertainty via a statistical bias correction technique. The bias correction successfully constrains the spatial SIT distribution and temporal variability in the CMIP5 projections whilst retaining the climatic fluctuations from individual ensemble members. The bias correction acts to reduce the uncertainty in projections of SIT and reveals the significant contributions of sea ice internal variability in the first half of the century and of scenario uncertainty from mid-century onwards. The projected date of ice-free conditions in the Arctic under the RCP8.5 high emission scenario occurs in the 2050s, which is a decade earlier than without the bias correction, with potentially significant implications for stakeholders in the Arctic such as the shipping industry. The bias correction methodology developed could be similarly applied to other variables to narrow uncertainty in climate projections more generally.
Improved Arctic sea ice thickness projections using bias-corrected CMIP5 simulations
Melia, N.; Haines, K.; Hawkins, E.
2015-12-01
Projections of Arctic sea ice thickness (SIT) have the potential to inform stakeholders about accessibility to the region, but are currently rather uncertain. The latest suite of CMIP5 global climate models (GCMs) produce a wide range of simulated SIT in the historical period (1979-2014) and exhibit various biases when compared with the Pan-Arctic Ice-Ocean Modelling and Assimilation System (PIOMAS) sea ice reanalysis. We present a new method to constrain such GCM simulations of SIT via a statistical bias correction technique. The bias correction successfully constrains the spatial SIT distribution and temporal variability in the CMIP5 projections whilst retaining the climatic fluctuations from individual ensemble members. The bias correction acts to reduce the spread in projections of SIT and reveals the significant contributions of climate internal variability in the first half of the century and of scenario uncertainty from the mid-century onwards. The projected date of ice-free conditions in the Arctic under the RCP8.5 high emission scenario occurs in the 2050s, which is a decade earlier than without the bias correction, with potentially significant implications for stakeholders in the Arctic such as the shipping industry. The bias correction methodology developed could be similarly applied to other variables to reduce spread in climate projections more generally.
Limited catching bias in a wild population of birds with near-complete census information.
Simons, Mirre J P; Winney, Isabel; Nakagawa, Shinichi; Burke, Terry; Schroeder, Julia
2015-08-01
Animal research often relies on catching wild animals; however, individuals may have different trappability, and this can generate bias. We studied bias in mist netting, the main method for catching wild birds. The unusually high resighting rate in our study population-house sparrows (Passer domesticus) on Lundy Island (England)-allowed us to obtain accurate estimates of the population size. This unique situation enabled us to test for catching bias in mist netting using deviations from the expected Poisson distribution. There was no evidence that a fraction of the birds in the population consistently remained uncaught. However, we detected a different bias: More birds than expected were captured only once within a year. This bias probably resulted from a mixture of fieldworkers sometimes ignoring rapid recaptures and birds becoming net shy after their first capture. We had sufficient statistical power with the available data to detect a substantial uncaught fraction. Therefore, our data are probably unbiased toward catching specific individuals from our population. Our analyses demonstrate that intensively monitored natural insular populations, in which population size can be estimated precisely, provide the potential to address important unanswered questions without concerns about a fraction of the population remaining uncaught. Our approach can help researchers to test for catching bias in closely monitored wild populations for which reliable estimates of population size and dispersal are available. PMID:26380681
Introducing Decorated HODs: modeling assembly bias in the galaxy-halo connection
Hearin, Andrew P.; Zentner, Andrew R.; van den Bosch, Frank C.; Campbell, Duncan; Tollerud, Erik
2016-05-01
The connection between galaxies and dark matter halos is often inferred from data using probabilistic models, such as the Halo Occupation Distribution (HOD). Conventional HOD formulations assume that only halo mass governs the galaxy-halo connection. Violations of this assumption, known as galaxy assembly bias, threaten the HOD program. We introduce decorated HODs, a new, flexible class of models designed to account for assembly bias. Decorated HODs minimally expand the parameter space and maximize the independence between traditional and novel HOD parameters. We use decorated HODs to quantify the influence of assembly bias on clustering and lensing statistics. For SDSS-like samples, the impact of assembly bias on galaxy clustering can be as large as a factor of two on r ˜ 200 kpc scales and ˜15% in the linear regime. Assembly bias can either enhance or diminish clustering on large scales, but generally increases clustering on scales r ≲ 1 Mpc. We performed our calculations with Halotools, an open-source, community-driven python package for studying the galaxy-halo connection (http://halotools.readthedocs.org). We conclude by describing the use of decorated HODs to treat assembly bias in otherwise conventional likelihood analyses.
Introducing decorated HODs: modelling assembly bias in the galaxy-halo connection
Hearin, Andrew P.; Zentner, Andrew R.; van den Bosch, Frank C.; Campbell, Duncan; Tollerud, Erik
2016-08-01
The connection between galaxies and dark matter haloes is often inferred from data using probabilistic models, such as the halo occupation distribution (HOD). Conventional HOD formulations assume that only halo mass governs the galaxy-halo connection. Violations of this assumption, known as galaxy assembly bias, threaten the HOD programme. We introduce decorated HODs, a new, flexible class of models designed to account for assembly bias. Decorated HODs minimally expand the parameter space and maximize the independence between traditional and novel HOD parameters. We use decorated HODs to quantify the influence of assembly bias on clustering and lensing statistics. For SDSS-like samples, the impact of assembly bias on galaxy clustering can be as large as a factor of 2 on r ˜ 200 kpc scales and ˜15 per cent in the linear regime. Assembly bias can either enhance or diminish clustering on large scales, but generally increases clustering on scales r ≲ 1 Mpc. We performed our calculations with HALOTOOLS, an open-source, community-driven PYTHON package for studying the galaxy-halo connection (http://halotools.readthedocs.org). We conclude by describing the use of decorated HODs to treat assembly bias in otherwise conventional likelihood analyses.
Systematic Biases in Parameter Estimation of Binary Black-Hole Mergers
Littenberg, Tyson B.; Baker, John G.; Buonanno, Alessandra; Kelly, Bernard J.
2012-01-01
Parameter estimation of binary-black-hole merger events in gravitational-wave data relies on matched filtering techniques, which, in turn, depend on accurate model waveforms. Here we characterize the systematic biases introduced in measuring astrophysical parameters of binary black holes by applying the currently most accurate effective-one-body templates to simulated data containing non-spinning numerical-relativity waveforms. For advanced ground-based detectors, we find that the systematic biases are well within the statistical error for realistic signal-to-noise ratios (SNR). These biases grow to be comparable to the statistical errors at high signal-to-noise ratios for ground-based instruments (SNR approximately 50) but never dominate the error budget. At the much larger signal-to-noise ratios expected for space-based detectors, these biases will become large compared to the statistical errors but are small enough (at most a few percent in the black-hole masses) that we expect they should not affect broad astrophysical conclusions that may be drawn from the data.
Bias-correction and Spatial Disaggregation for Climate Change Impact Assessments at a basin scale
Nyunt, Cho; Koike, Toshio; Yamamoto, Akio; Nemoto, Toshihoro; Kitsuregawa, Masaru
2013-04-01
Basin-scale climate change impact studies mainly rely on general circulation models (GCMs) comprising the related emission scenarios. Realistic and reliable data from GCM is crucial for national scale or basin scale impact and vulnerability assessments to build safety society under climate change. However, GCM fail to simulate regional climate features due to the imprecise parameterization schemes in atmospheric physics and coarse resolution scale. This study describes how to exclude some unsatisfactory GCMs with respect to focused basin, how to minimize the biases of GCM precipitation through statistical bias correction and how to cover spatial disaggregation scheme, a kind of downscaling, within in a basin. GCMs rejection is based on the regional climate features of seasonal evolution as a bench mark and mainly depends on spatial correlation and root mean square error of precipitation and atmospheric variables over the target region. Global Precipitation Climatology Project (GPCP) and Japanese 25-uear Reanalysis Project (JRA-25) are specified as references in figuring spatial pattern and error of GCM. Statistical bias-correction scheme comprises improvements of three main flaws of GCM precipitation such as low intensity drizzled rain days with no dry day, underestimation of heavy rainfall and inter-annual variability of local climate. Biases of heavy rainfall are conducted by generalized Pareto distribution (GPD) fitting over a peak over threshold series. Frequency of rain day error is fixed by rank order statistics and seasonal variation problem is solved by using a gamma distribution fitting in each month against insi-tu stations vs. corresponding GCM grids. By implementing the proposed bias-correction technique to all insi-tu stations and their respective GCM grid, an easy and effective downscaling process for impact studies at the basin scale is accomplished. The proposed method have been examined its applicability to some of the basins in various climate
Natural-gas futures: Bias, predictive performance, and the theory of storage
International Nuclear Information System (INIS)
This study reports several empirical findings concerning natural gas futures prices. First, spot and futures prices are non-stationary and the observed trends are due to positive drifts in the random-walk components of the prices rather than possible deterministic time trends. Second, market forecast errors are stationary. Third, futures are less than expected future spot prices so that futures are backdated. Fourth, the bias in the futures prices is time varying. Fifth, futures have statistically significant market-timing ability, despite the bias in the magnitude forecasts. Finally, the data lends partial support to the cost-of-carry theory of the basis determination. (Author)
Statistical tests of nonparametric hypotheses asymptotic theory
Pons, Odile
2013-01-01
An overview of the asymptotic theory of optimal nonparametric tests is presented in this book. It covers a wide range of topics: Neyman-Pearson and LeCam's theories of optimal tests, the theories of empirical processes and kernel estimators with extensions of their applications to the asymptotic behavior of tests for distribution functions, densities and curves of the nonparametric models defining the distributions of point processes and diffusions. With many new test statistics developed for smooth curves, the reliance on kernel estimators with bias corrections and the weak convergence of the
Escaping RGBland: Selecting Colors for Statistical Graphics
Zeileis, Achim; Hornik, Kurt; Murrell, Paul
2007-01-01
Statistical graphics are often augmented by the use of color coding information contained in some variable. When this involves the shading of areas (and not only points or lines) - e.g., as in bar plots, pie charts, mosaic displays or heatmaps - it is important that the colors are perceptually based and do not introduce optical illusions or systematic bias. Here, we discuss how the perceptually-based Hue-Chroma-Luminance (HCL) color space can be used for deriving suitable color palettes for c...
Choosing Color Palettes for Statistical Graphics
Zeileis, Achim; Hornik, Kurt
2006-01-01
Statistical graphics are often augmented by the use of color coding information contained in some variable. When this involves the shading of areas (and not only points or lines) - e.g., as in bar plots, pie charts, mosaic displays or heatmaps - it is important that the colors are perceptually based and do not introduce optical illusions or systematic bias. Here, we discuss how the perceptually-based Hue-Chroma-Luminance (HCL) color space can be used for deriving suitable color palettes for c...
Contextual modulation of biases in face recognition.
Directory of Open Access Journals (Sweden)
Fatima Maria Felisberti
Full Text Available BACKGROUND: The ability to recognize the faces of potential cooperators and cheaters is fundamental to social exchanges, given that cooperation for mutual benefit is expected. Studies addressing biases in face recognition have so far proved inconclusive, with reports of biases towards faces of cheaters, biases towards faces of cooperators, or no biases at all. This study attempts to uncover possible causes underlying such discrepancies. METHODOLOGY AND FINDINGS: Four experiments were designed to investigate biases in face recognition during social exchanges when behavioral descriptors (prosocial, antisocial or neutral embedded in different scenarios were tagged to faces during memorization. Face recognition, measured as accuracy and response latency, was tested with modified yes-no, forced-choice and recall tasks (N = 174. An enhanced recognition of faces tagged with prosocial descriptors was observed when the encoding scenario involved financial transactions and the rules of the social contract were not explicit (experiments 1 and 2. Such bias was eliminated or attenuated by making participants explicitly aware of "cooperative", "cheating" and "neutral/indifferent" behaviors via a pre-test questionnaire and then adding such tags to behavioral descriptors (experiment 3. Further, in a social judgment scenario with descriptors of salient moral behaviors, recognition of antisocial and prosocial faces was similar, but significantly better than neutral faces (experiment 4. CONCLUSION: The results highlight the relevance of descriptors and scenarios of social exchange in face recognition, when the frequency of prosocial and antisocial individuals in a group is similar. Recognition biases towards prosocial faces emerged when descriptors did not state the rules of a social contract or the moral status of a behavior, and they point to the existence of broad and flexible cognitive abilities finely tuned to minor changes in social context.
COSMOS: STOCHASTIC BIAS FROM MEASUREMENTS OF WEAK LENSING AND GALAXY CLUSTERING
International Nuclear Information System (INIS)
In the theory of structure formation, galaxies are biased tracers of the underlying matter density field. The statistical relation between galaxy and matter density field is commonly referred to as galaxy bias. In this paper, we test the linear bias model with weak-lensing and galaxy clustering measurements in the 2 deg2 COSMOS field. We estimate the bias of galaxies between redshifts z = 0.2 and z = 1 and over correlation scales between R = 0.2 h–1 Mpc and R = 15 h–1 Mpc. We focus on three galaxy samples, selected in flux (simultaneous cuts I814W s 9 * 10 h–2 M☉ and 1010 * 11 h–2 M☉). At scales R > 2 h–1 Mpc, our measurements support a model of bias increasing with redshift. The Tinker et al. fitting function provides a good fit to the data. We find the best-fit mass of the galaxy halos to be log (M200/h–1 M☉) = 11.7+0.6–1.3 and log (M200/h–1 M☉) = 12.4+0.2–2.9, respectively, for the low and high stellar-mass samples. In the halo model framework, bias is scale dependent with a change of slope at the transition scale between the one and the two halo terms. We detect a scale dependence of bias with a turndown at scale R = 2.3 ± 1.5 h–1 Mpc, in agreement with previous galaxy clustering studies. We find no significant amount of stochasticity, suggesting that a linear bias model is sufficient to describe our data. We use N-body simulations to quantify both the amount of cosmic variance and systematic errors in the measurement.
Spatial Statistical Data Fusion (SSDF)
Braverman, Amy J.; Nguyen, Hai M.; Cressie, Noel
2013-01-01
As remote sensing for scientific purposes has transitioned from an experimental technology to an operational one, the selection of instruments has become more coordinated, so that the scientific community can exploit complementary measurements. However, tech nological and scientific heterogeneity across devices means that the statistical characteristics of the data they collect are different. The challenge addressed here is how to combine heterogeneous remote sensing data sets in a way that yields optimal statistical estimates of the underlying geophysical field, and provides rigorous uncertainty measures for those estimates. Different remote sensing data sets may have different spatial resolutions, different measurement error biases and variances, and other disparate characteristics. A state-of-the-art spatial statistical model was used to relate the true, but not directly observed, geophysical field to noisy, spatial aggregates observed by remote sensing instruments. The spatial covariances of the true field and the covariances of the true field with the observations were modeled. The observations are spatial averages of the true field values, over pixels, with different measurement noise superimposed. A kriging framework is used to infer optimal (minimum mean squared error and unbiased) estimates of the true field at point locations from pixel-level, noisy observations. A key feature of the spatial statistical model is the spatial mixed effects model that underlies it. The approach models the spatial covariance function of the underlying field using linear combinations of basis functions of fixed size. Approaches based on kriging require the inversion of very large spatial covariance matrices, and this is usually done by making simplifying assumptions about spatial covariance structure that simply do not hold for geophysical variables. In contrast, this method does not require these assumptions, and is also computationally much faster. This method is
Optimization techniques in statistics
Rustagi, Jagdish S
1994-01-01
Statistics help guide us to optimal decisions under uncertainty. A large variety of statistical problems are essentially solutions to optimization problems. The mathematical techniques of optimization are fundamentalto statistical theory and practice. In this book, Jagdish Rustagi provides full-spectrum coverage of these methods, ranging from classical optimization and Lagrange multipliers, to numerical techniques using gradients or direct search, to linear, nonlinear, and dynamic programming using the Kuhn-Tucker conditions or the Pontryagin maximal principle. Variational methods and optimiza
Equilibrium statistical mechanics
Mayer, J E
1968-01-01
The International Encyclopedia of Physical Chemistry and Chemical Physics, Volume 1: Equilibrium Statistical Mechanics covers the fundamental principles and the development of theoretical aspects of equilibrium statistical mechanics. Statistical mechanical is the study of the connection between the macroscopic behavior of bulk matter and the microscopic properties of its constituent atoms and molecules. This book contains eight chapters, and begins with a presentation of the master equation used for the calculation of the fundamental thermodynamic functions. The succeeding chapters highlight t
Lectures on statistical mechanics
Bowler, M G
1982-01-01
Anyone dissatisfied with the almost ritual dullness of many 'standard' texts in statistical mechanics will be grateful for the lucid explanation and generally reassuring tone. Aimed at securing firm foundations for equilibrium statistical mechanics, topics of great subtlety are presented transparently and enthusiastically. Very little mathematical preparation is required beyond elementary calculus and prerequisites in physics are limited to some elementary classical thermodynamics. Suitable as a basis for a first course in statistical mechanics, the book is an ideal supplement to more convent
Mathematical statistics with applications
Wackerly, Dennis D; Scheaffer, Richard L
2008-01-01
In their bestselling MATHEMATICAL STATISTICS WITH APPLICATIONS, premiere authors Dennis Wackerly, William Mendenhall, and Richard L. Scheaffer present a solid foundation in statistical theory while conveying the relevance and importance of the theory in solving practical problems in the real world. The authors' use of practical applications and excellent exercises helps you discover the nature of statistics and understand its essential role in scientific research.
Δάμη, Μαρία; Vella, Alfred
1988-01-01
The problem of misuse of statistical packages and hence statistical methods has long peen recognised but no real solution has yet appeared, although some useful work has been done in related fields. This problem appears to lend itself to expert system technology. This paper outlines the history of research in statistical expert systems, showing how the demands of data analysis are different from those of other fields. Furthermore, the paper reviews some recent work and discu...
Mahalanobis, P C
1965-01-01
Contributions to Statistics focuses on the processes, methodologies, and approaches involved in statistics. The book is presented to Professor P. C. Mahalanobis on the occasion of his 70th birthday. The selection first offers information on the recovery of ancillary information and combinatorial properties of partially balanced designs and association schemes. Discussions focus on combinatorial applications of the algebra of association matrices, sample size analogy, association matrices and the algebra of association schemes, and conceptual statistical experiments. The book then examines latt
Applied statistics for economists
Lewis, Margaret
2012-01-01
This book is an undergraduate text that introduces students to commonly-used statistical methods in economics. Using examples based on contemporary economic issues and readily-available data, it not only explains the mechanics of the various methods, it also guides students to connect statistical results to detailed economic interpretations. Because the goal is for students to be able to apply the statistical methods presented, online sources for economic data and directions for performing each task in Excel are also included.
Bradley, Robert K.; Adam Roberts; Michael Smoot; Sudeep Juvekar; Jaeyoung Do; Colin Dewey; Ian Holmes; Lior Pachter
2009-01-01
We describe a new program for the alignment of multiple biological sequences that is both statistically motivated and fast enough for problem sizes that arise in practice. Our Fast Statistical Alignment program is based on pair hidden Markov models which approximate an insertion/deletion process on a tree and uses a sequence annealing algorithm to combine the posterior probabilities estimated from these models into a multiple alignment. FSA uses its explicit statistical model to produce multi...
Rosenbaum, Paul R.
1991-01-01
Statistics or functions are discussed that measure agreement between certain types of partially ordered data. These poset statistics are a generalization of two familiar classes of functions: the arrangement increasing functions and the decreasing reflection functions; those functions measure agreement between linearly ordered data. Specifically, the statistics in question are functions $h(\\mathbf{X}_1, \\mathbf{X}_2)$ of two matrix arguments, each having $N$ rows and they measure the agreemen...
Equilibrium statistical mechanics
Jackson, E Atlee
2000-01-01
Ideal as an elementary introduction to equilibrium statistical mechanics, this volume covers both classical and quantum methodology for open and closed systems. Introductory chapters familiarize readers with probability and microscopic models of systems, while additional chapters describe the general derivation of the fundamental statistical mechanics relationships. The final chapter contains 16 sections, each dealing with a different application, ordered according to complexity, from classical through degenerate quantum statistical mechanics. Key features include an elementary introduction t
Statistical Methods for Astronomy
Feigelson, Eric D.; Babu, G. Jogesh
2012-01-01
This review outlines concepts of mathematical statistics, elements of probability theory, hypothesis tests and point estimation for use in the analysis of modern astronomical data. Least squares, maximum likelihood, and Bayesian approaches to statistical inference are treated. Resampling methods, particularly the bootstrap, provide valuable procedures when distributions functions of statistics are not known. Several approaches to model selection and good- ness of fit are considered. Applied s...
Significance analysis of lexical bias in microarray data
Directory of Open Access Journals (Sweden)
Falkow Stanley
2003-04-01
Full Text Available Abstract Background Genes that are determined to be significantly differentially regulated in microarray analyses often appear to have functional commonalities, such as being components of the same biochemical pathway. This results in certain words being under- or overrepresented in the list of genes. Distinguishing between biologically meaningful trends and artifacts of annotation and analysis procedures is of the utmost importance, as only true biological trends are of interest for further experimentation. A number of sophisticated methods for identification of significant lexical trends are currently available, but these methods are generally too cumbersome for practical use by most microarray users. Results We have developed a tool, LACK, for calculating the statistical significance of apparent lexical bias in microarray datasets. The frequency of a user-specified list of search terms in a list of genes which are differentially regulated is assessed for statistical significance by comparison to randomly generated datasets. The simplicity of the input files and user interface targets the average microarray user who wishes to have a statistical measure of apparent lexical trends in analyzed datasets without the need for bioinformatics skills. The software is available as Perl source or a Windows executable. Conclusion We have used LACK in our laboratory to generate biological hypotheses based on our microarray data. We demonstrate the program's utility using an example in which we confirm significant upregulation of SPI-2 pathogenicity island of Salmonella enterica serovar Typhimurium by the cation chelator dipyridyl.
Everyday probability and statistics health, elections, gambling and war
Woolfson, Michael Mark
2012-01-01
Probability and statistics impinge on the life of the average person in a variety of ways - as is suggested by the title of this book. Very often information is provided that is factually accurate but intended to give a biased view. This book presents the important results of probability and statistics without making heavy mathematical demands on the reader. It should enable an intelligent reader to properly assess statistical information and to understand that the same information can be presented in different ways.In this second edition the author presents a new chapter exploring science and
Social biases determine spatiotemporal sparseness of ciliate mating heuristics.
Clark, Kevin B
2012-01-01
Ciliates become highly social, even displaying animal-like qualities, in the joint presence of aroused conspecifics and nonself mating pheromones. Pheromone detection putatively helps trigger instinctual and learned courtship and dominance displays from which social judgments are made about the availability, compatibility, and fitness representativeness or likelihood of prospective mates and rivals. In earlier studies, I demonstrated the heterotrich Spirostomum ambiguum improves mating competence by effecting preconjugal strategies and inferences in mock social trials via behavioral heuristics built from Hebbian-like associative learning. Heuristics embody serial patterns of socially relevant action that evolve into ordered, topologically invariant computational networks supporting intra- and intermate selection. S. ambiguum employs heuristics to acquire, store, plan, compare, modify, select, and execute sets of mating propaganda. One major adaptive constraint over formation and use of heuristics involves a ciliate's initial subjective bias, responsiveness, or preparedness, as defined by Stevens' Law of subjective stimulus intensity, for perceiving the meaningfulness of mechanical pressures accompanying cell-cell contacts and additional perimating events. This bias controls durations and valences of nonassociative learning, search rates for appropriate mating strategies, potential net reproductive payoffs, levels of social honesty and deception, successful error diagnosis and correction of mating signals, use of insight or analysis to solve mating dilemmas, bioenergetics expenditures, and governance of mating decisions by classical or quantum statistical mechanics. I now report this same social bias also differentially affects the spatiotemporal sparseness, as measured with metric entropy, of ciliate heuristics. Sparseness plays an important role in neural systems through optimizing the specificity, efficiency, and capacity of memory representations. The present
Record Statistics and Dynamics
DEFF Research Database (Denmark)
Sibani, Paolo; Jensen, Henrik J.
2009-01-01
The term record statistics covers the statistical properties of records within an ordered series of numerical data obtained from observations or measurements. A record within such series is simply a value larger (or smaller) than all preceding values. The mathematical properties of records strongly...... fluctuations of e. g. the energy are able to push the system past some sort of ‘edge of stability’, inducing irreversible configurational changes, whose statistics then closely follows the statistics of record fluctuations....
Kanji, Gopal K
2006-01-01
This expanded and updated Third Edition of Gopal K. Kanji's best-selling resource on statistical tests covers all the most commonly used tests with information on how to calculate and interpret results with simple datasets. Each entry begins with a short summary statement about the test's purpose, and contains details of the test objective, the limitations (or assumptions) involved, a brief outline of the method, a worked example, and the numerical calculation. 100 Statistical Tests, Third Edition is the one indispensable guide for users of statistical materials and consumers of statistical information at all levels and across all disciplines.
Boslaugh, Sarah
2008-01-01
Need to learn statistics as part of your job, or want some help passing a statistics course? Statistics in a Nutshell is a clear and concise introduction and reference that's perfect for anyone with no previous background in the subject. This book gives you a solid understanding of statistics without being too simple, yet without the numbing complexity of most college texts. You get a firm grasp of the fundamentals and a hands-on understanding of how to apply them before moving on to the more advanced material that follows. Each chapter presents you with easy-to-follow descriptions illustrat
International Nuclear Information System (INIS)
The quantum statistics of charged, extremal black holes is investigated beginning with the hypothesis that the quantum state is a functional on the space of closed three-geometries, with each black hole connected to an oppositely charged black hole through a spatial wormhole. From this starting point a simple argument is given that a collection of extremal black holes obeys neither Bose nor Fermi statistics. Rather, they obey an exotic variety of particle statistics known as ''infinite statistics'' which resembles that of distinguishable particles and is realized by a q deformation of the quantum commutation relations
Annual Statistical Supplement, 2015
Social Security Administration — The Annual Statistical Supplement, 2015 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
Annual Statistical Supplement, 2011
Social Security Administration — The Annual Statistical Supplement, 2011 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
Annual Statistical Supplement, 2003
Social Security Administration — The Annual Statistical Supplement, 2003 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
Annual Statistical Supplement, 2004
Social Security Administration — The Annual Statistical Supplement, 2004 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
Annual Statistical Supplement, 2008
Social Security Administration — The Annual Statistical Supplement, 2008 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
Annual Statistical Supplement, 2002
Social Security Administration — The Annual Statistical Supplement, 2002 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
Annual Statistical Supplement, 2001
Social Security Administration — The Annual Statistical Supplement, 2001 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
Annual Statistical Supplement, 2006
Social Security Administration — The Annual Statistical Supplement, 2006 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
Annual Statistical Supplement, 2000
Social Security Administration — The Annual Statistical Supplement, 2000 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
Fan, Jianqing
2006-01-01
During the last two decades, many areas of statistical inference have experienced phenomenal growth. This book presents a timely analysis and overview of some of these new developments and a contemporary outlook on the various frontiers of statistics.Eminent leaders in the field have contributed 16 review articles and 6 research articles covering areas including semi-parametric models, data analytical nonparametric methods, statistical learning, network tomography, longitudinal data analysis, financial econometrics, time series, bootstrap and other re-sampling methodologies, statistical comput
Annual Statistical Supplement, 2009
Social Security Administration — The Annual Statistical Supplement, 2009 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
Annual Statistical Supplement, 2010
Social Security Administration — The Annual Statistical Supplement, 2010 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
Schieve, William C.; Horwitz, Lawrence P.
2009-04-01
1. Foundations of quantum statistical mechanics; 2. Elementary examples; 3. Quantum statistical master equation; 4. Quantum kinetic equations; 5. Quantum irreversibility; 6. Entropy and dissipation: the microscopic theory; 7. Global equilibrium: thermostatics and the microcanonical ensemble; 8. Bose-Einstein ideal gas condensation; 9. Scaling, renormalization and the Ising model; 10. Relativistic covariant statistical mechanics of many particles; 11. Quantum optics and damping; 12. Entanglements; 13. Quantum measurement and irreversibility; 14. Quantum Langevin equation: quantum Brownian motion; 15. Linear response: fluctuation and dissipation theorems; 16. Time dependent quantum Green's functions; 17. Decay scattering; 18. Quantum statistical mechanics, extended; 19. Quantum transport with tunneling and reservoir ballistic transport; 20. Black hole thermodynamics; Appendix; Index.
Ariwahjoedi, Seramika; Kosasih, Jusak Sali; Rovelli, Carlo; Zen, Freddy Permana
2016-01-01
Following our earlier work, we construct statistical discrete geometry by applying statistical mechanics to discrete (Regge) gravity. We propose a coarse-graining method for discrete geometry under the assumptions of atomism and background independence. To maintain these assumptions, restrictions are given to the theory by introducing cut-offs, both in ultraviolet and infrared regime. Having a well-defined statistical picture of discrete Regge geometry, we take the infinite degrees of freedom (large n) limit. We argue that the correct limit consistent with the restrictions and the background independence concept is not the continuum limit of statistical mechanics, but the thermodynamical limit.
Discovering statistics using SPSS
Field, Andy
2007-01-01
'In this brilliant new edition Andy Field has introduced important new introductory material on statistics that the student will need and was missing at least in the first edition. This book is the best blend that I know of a textbook in statistics and a manual on SPSS. It is a balanced composite of both topics, using SPSS to illustrate important statistical material and, through graphics, to make visible important approaches to data analysis. There are many places in the book where I had to laugh, and that's saying a lot for a book on statistics. His excellent style engages the reader and mak
Annual Statistical Supplement, 2007
Social Security Administration — The Annual Statistical Supplement, 2007 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
Annual Statistical Supplement, 2014
Social Security Administration — The Annual Statistical Supplement, 2014 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
Annual Statistical Supplement, 2005
Social Security Administration — The Annual Statistical Supplement, 2005 includes the most comprehensive data available on the Social Security and Supplemental Security Income programs. More than...
Understanding Computational Bayesian Statistics
Bolstad, William M
2011-01-01
A hands-on introduction to computational statistics from a Bayesian point of view Providing a solid grounding in statistics while uniquely covering the topics from a Bayesian perspective, Understanding Computational Bayesian Statistics successfully guides readers through this new, cutting-edge approach. With its hands-on treatment of the topic, the book shows how samples can be drawn from the posterior distribution when the formula giving its shape is all that is known, and how Bayesian inferences can be based on these samples from the posterior. These ideas are illustrated on common statistic
Bulmer, M G
1979-01-01
There are many textbooks which describe current methods of statistical analysis, while neglecting related theory. There are equally many advanced textbooks which delve into the far reaches of statistical theory, while bypassing practical applications. But between these two approaches is an unfilled gap, in which theory and practice merge at an intermediate level. Professor M. G. Bulmer's Principles of Statistics, originally published in 1965, was created to fill that need. The new, corrected Dover edition of Principles of Statistics makes this invaluable mid-level text available once again fo
Finding seeds for segmentation using statistical fusion
Xing, Fangxu; Asman, Andrew J.; Prince, Jerry L.; Landman, Bennett A.
2012-02-01
Image labeling is an essential step for quantitative analysis of medical images. Many image labeling algorithms require seed identification in order to initialize segmentation algorithms such as region growing, graph cuts, and the random walker. Seeds are usually placed manually by human raters, which makes these algorithms semi-automatic and can be prohibitive for very large datasets. In this paper an automatic algorithm for placing seeds using multi-atlas registration and statistical fusion is proposed. Atlases containing the centers of mass of a collection of neuroanatomical objects are deformably registered in a training set to determine where these centers of mass go after labels transformed by registration. The biases of these transformations are determined and incorporated in a continuous form of Simultaneous Truth And Performance Level Estimation (STAPLE) fusion, thereby improving the estimates (on average) over a single registration strategy that does not incorporate bias or fusion. We evaluate this technique using real 3D brain MR image atlases and demonstrate its efficacy on correcting the data bias and reducing the fusion error.
Energy Technology Data Exchange (ETDEWEB)
Makhnovskii, Yurii A. [Topchiev Institute of Petrochemical Synthesis, Russian Academy of Sciences, Leninsky Prospect 29, Moscow 119991 (Russian Federation); Berezhkovskii, Alexander M. [Mathematical and Statistical Computing Laboratory, Division of Computational Bioscience, Center for Information Technology, National Institutes of Health, Bethesda, Maryland 20819 (United States); Antipov, Anatoly E. [Faculty of Fundamental Physics and Chemical Engineering, Moscow State University, GSP-1, 1-51 Leninskie Gory, Moscow 119991 (Russian Federation); Zitserman, Vladimir Yu. [Joint Institute for High Temperatures, Russian Academy of Sciences, Izhorskaya 13, Bldg. 2, Moscow 125412 (Russian Federation)
2015-11-07
This paper is devoted to particle transport in a tube formed by alternating wide and narrow sections, in the presence of an external biasing force. The focus is on the effective transport coefficients—mobility and diffusivity, as functions of the biasing force and the geometric parameters of the tube. Dependences of the effective mobility and diffusivity on the tube geometric parameters are known in the limiting cases of no bias and strong bias. The approximations used to obtain these results are inapplicable at intermediate values of the biasing force. To bridge the two limits Brownian dynamics simulations were run to determine the transport coefficients at intermediate values of the force. The simulations were performed for a representative set of tube geometries over a wide range of the biasing force. They revealed that there is a range of the narrow section length, where the force dependence of the mobility has a maximum. In contrast, the diffusivity is a monotonically increasing function of the force. A simple formula is proposed, which reduces to the known dependences of the diffusivity on the tube geometric parameters in both limits of zero and strong bias. At intermediate values of the biasing force, the formula catches the diffusivity dependence on the narrow section length, if the radius of these sections is not too small.
Strick, M.A.; Stoeckart, P.F.; Dijksterhuis, A.J.
2015-01-01
It is a common research finding that conscious thought helps people to avoid racial discrimination. These three experiments, however, illustrate that conscious thought may increase biased face memory, which leads to increased judgment bias (i.e., preferring White to Black individuals). In Experiment
Placebo effect studies are susceptible to response bias and to other types of biases
DEFF Research Database (Denmark)
Hróbjartsson, Asbjørn; Kaptchuk, Ted J; Miller, Franklin G
2011-01-01
Investigations of the effect of placebo are often challenging to conduct and interpret. The history of placebo shows that assessment of its clinical significance has a real potential to be biased. We analyze and discuss typical types of bias in studies on placebo....
Subhalo abundance matching and assembly bias in the EAGLE simulation
Chaves-Montero, Jonás; Angulo, Raul E.; Schaye, Joop; Schaller, Matthieu; Crain, Robert A.; Furlong, Michelle; Theuns, Tom
2016-08-01
Subhalo abundance matching (SHAM) is a widely used method to connect galaxies with dark matter structures in numerical simulations. SHAM predictions agree remarkably well with observations, yet they still lack strong theoretical support. We examine the performance, implementation, and assumptions of SHAM using the `Evolution and Assembly of Galaxies and their Environment' (EAGLE) project simulations. We find that Vrelax, the highest value of the circular velocity attained by a subhalo while it satisfies a relaxation criterion, is the subhalo property that correlates most strongly with galaxy stellar mass (Mstar). Using this parameter in SHAM, we retrieve the real-space clustering of EAGLE to within our statistical uncertainties on scales greater than 2 Mpc for galaxies with 8.77 assembly bias. We demonstrate assembly bias alters the clustering in EAGLE by 20 per cent and Vrelax captures its effect to within 15 per cent. We trace small differences in the clustering to the failure of SHAM as typically implemented, i.e. the Mstar assigned to a subhalo does not depend on (i) its host halo mass, (ii) whether it is a central or a satellite. In EAGLE, we find that these assumptions are not completely satisfied.
Validation of models with constant bias: an applied approach
Directory of Open Access Journals (Sweden)
Salvador Medina-Peralta
2014-06-01
Full Text Available Objective. This paper presents extensions to the statistical validation method based on the procedure of Freese when a model shows constant bias (CB in its predictions and illustrate the method with data from a new mechanistic model that predict weight gain in cattle. Materials and methods. The extensions were the hypothesis tests and maximum anticipated error for the alternative approach, and the confidence interval for a quantile of the distribution of errors. Results. The model evaluated showed CB, once the CB is removed and with a confidence level of 95%, the magnitude of the error does not exceed 0.575 kg. Therefore, the validated model can be used to predict the daily weight gain of cattle, although it will require an adjustment in its structure based on the presence of CB to increase the accuracy of its forecasts. Conclusions. The confidence interval for the 1-α quantile of the distribution of errors after correcting the constant bias, allows determining the top limit for the magnitude of the error of prediction and use it to evaluate the evolution of the model in the forecasting of the system. The confidence interval approach to validate a model is more informative than the hypothesis tests for the same purpose.
Python for probability, statistics, and machine learning
Unpingco, José
2016-01-01
This book covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules in these areas. The entire text, including all the figures and numerical results, is reproducible using the Python codes and their associated Jupyter/IPython notebooks, which are provided as supplementary downloads. The author develops key intuitions in machine learning by working meaningful examples using multiple analytical methods and Python codes, thereby connecting theoretical concepts to concrete implementations. Modern Python modules like Pandas, Sympy, and Scikit-learn are applied to simulate and visualize important machine learning concepts like the bias/variance trade-off, cross-validation, and regularization. Many abstract mathematical ideas, such as convergence in probability theory, are developed and illustrated with numerical examples. This book is suitable for anyone with an undergraduate-level exposure to probability, statistics, or machine learning and with rudimentary knowl...
Statistical error analysis of reactivity measurement
Energy Technology Data Exchange (ETDEWEB)
Thammaluckan, Sithisak; Hah, Chang Joo [KEPCO International Nuclear Graduate School, Ulsan (Korea, Republic of)
2013-10-15
After statistical analysis, it was confirmed that each group were sampled from same population. It is observed in Table 7 that the mean error decreases as core size increases. Application of bias factor obtained from this research reduces mean error further. The point kinetic model had been used to measure control rod worth without 3D spatial information of neutron flux or power distribution, which causes inaccurate result. Dynamic Control rod Reactivity Measurement (DCRM) was employed to take into account of 3D spatial information of flux in the point kinetics model. The measured bank worth probably contains some uncertainty such as methodology uncertainty and measurement uncertainty. Those uncertainties may varies with size of core and magnitude of reactivity. The goal of this research is to investigate the effect of core size and magnitude of control rod worth on the error of reactivity measurement using statistics.
Grandfather regulations, new source bias, and state air toxics regulations
International Nuclear Information System (INIS)
This paper uses plant-level data from the Census of Manufactures and the variation in toxic air pollution regulations across states to measure the effects of laws that are more stringent for new sources of pollution than for existing sources (so-called 'grandfather' regulations). Of particular interest is the resulting 'new source bias' and its effects on capital vintage and investment. Two industries are examined: commercial printing, which has a local product market; and paint manufacturing, which has a more national market. In general, there seem to be no statistically significant differences in capital vintage or investment between plants in states that grandfather new sources of pollution, plants in states that have no air toxics regulations, and plants in states that regulate both new and existing sources
Ascertainment bias in studies of human genome-wide polymorphism
DEFF Research Database (Denmark)
Clark, Andrew G.; Hubisz, Melissa J.; Bustamente, Carlos D.;
2005-01-01
SNPs that are found are influenced by the discovery sampling effort. The International HapMap project relied on nearly any piece of information available to identify SNPs-including BAC end sequences, shotgun reads, and differences between public and private sequences-and even made use of chimpanzee...... resequencing-by-hybridization effort using the 24 people of diverse origin in the Polymorphism Discovery Resource. Here we take these two data sets and contrast two basic summary statistics, heterozygosity and FST, as well as the site frequency spectra, for 500-kb windows spanning the genome. The magnitude of...... studies. However, discrepancies persist, suggesting that the heterogeneity in the SNP discovery process of the HapMap project resulted in a data set resistant to complete ascertainment correction. Ascertainment bias will likely erode the power of tests of association between SNPs and complex disorders...
Lensing Bias to CMB Measurements of Compensated Isocurvature Perturbations
Heinrich, Chen He; Hu, Wayne
2016-01-01
Compensated isocurvature perturbations (CIPs) are modes in which the baryon and dark matter density fluctuations cancel. They arise in the curvaton scenario as well as some models of baryogenesis. While they leave no observable effects on the cosmic microwave background (CMB) at linear order, they do spatially modulate two-point CMB statistics and can be reconstructed in a manner similar to gravitational lensing. Due to the similarity between the effects of CMB lensing and CIPs, lensing contributes nearly Gaussian random noise to the CIP estimator that approximately doubles the reconstruction noise power. Additionally, the cross correlation between lensing and the integrated Sachs-Wolfe (ISW) effect generates a correlation between the CIP estimator and the temperature field even in the absence of a correlated CIP signal. For cosmic-variance limited temperature measurements out to multipoles $l \\leq 2500$, subtracting a fixed lensing bias degrades the detection threshold for CIPs by a factor of $1.3$, whether ...
Reciprocity-induced bias in digital reputation
Livan, Giacomo; Aste, Tomaso
2016-01-01
The peer-to-peer (P2P) economy relies on establishing trust in distributed networked systems, where the reliability of a user is assessed through digital peer-review processes that aggregate ratings into reputation scores. Here we present evidence of a network effect which biases the digital reputations of the users of P2P networks, showing that P2P networks display exceedingly high levels of reciprocity. In fact, these are so large that they are close to the highest levels structurally compatible with the networks' reputation landscape. This shows that the crowdsourcing process underpinning digital reputation is significantly distorted by the attempt of users to mutually boost reputation, or to retaliate, through the exchange of ratings. We show that the least active users are predominantly responsible for such reciprocity-induced bias, and that this fact can be exploited to suppress the bias itself.
Motion, identity and the bias toward agency
Directory of Open Access Journals (Sweden)
Chris eFields
2014-08-01
Full Text Available The well-documented human bias toward agency as a cause and therefore an explanation of observed events is typically attributed to evolutionary selection for a social brain. Based on a review of developmental and adult behavioral and neurocognitive data, it is argued that the bias toward agency is a result of the default human solution, developed during infancy, to the computational requirements of object re-identification over gaps in observation of more than a few seconds. If this model is correct, overriding the bias toward agency to construct mechanistic explanations of observed events requires structure-mapping inferences, implemented by the pre-motor action planning system, that replace agents with mechanisms as causes of unobserved changes in contextual or featural properties of objects. Experiments that would test this model are discussed.
Recognition bias and the physical attractiveness stereotype.
Rohner, Jean-Christophe; Rasmussen, Anders
2012-06-01
Previous studies have found a recognition bias for information consistent with the physical attractiveness stereotype (PAS), in which participants believe that they remember that attractive individuals have positive qualities and that unattractive individuals have negative qualities, regardless of what information actually occurred. The purpose of this research was to examine whether recognition bias for PAS congruent information is replicable and invariant across a variety of conditions (i.e. generalizable). The effects of nine different moderator variables were examined in two experiments. With a few exceptions, the effect of PAS congruence on recognition bias was independent of the moderator variables. The results suggest that the tendency to believe that one remembers information consistent with the physical attractiveness stereotype is a robust phenomenon. PMID:22416805
Recursive bias estimation for high dimensional smoothers
Energy Technology Data Exchange (ETDEWEB)
Hengartner, Nicolas W [Los Alamos National Laboratory; Matzner-lober, Eric [UHB, FRANCE; Cornillon, Pierre - Andre [INRA
2008-01-01
In multivariate nonparametric analysis, sparseness of the covariates also called curse of dimensionality, forces one to use large smoothing parameters. This leads to biased smoothers. Instead of focusing on optimally selecting the smoothing parameter, we fix it to some reasonably large value to ensure an over-smoothing of the data. The resulting smoother has a small variance but a substantial bias. In this paper, we propose to iteratively correct the bias initial estimator by an estimate of the latter obtained by smoothing the residuals. We examine in detail the convergence of the iterated procedure for classical smoothers and relate our procedure to L{sub 2}-Boosting. We apply our method to simulated and real data and show that our method compares favorably with existing procedures.
Systematic approach to establishing criticality biases
International Nuclear Information System (INIS)
A systematic approach has been developed to determine benchmark biases and apply those biases to code results to meet the requirements of DOE Order 5480.24 regarding documenting criticality safety margins. Previously, validation of the code against experimental benchmarks to prove reasonable agreement was sufficient. However, DOE Order 5480.24 requires contractors to adhere to the requirements of ANSI/ANS-8.1 and establish subcritical margins. A method was developed to incorporate biases and uncertainties from benchmark calculations into a keff value with quantifiable uncertainty. The method produces a 95% confidence level in both the keff value of the scenario modeled and the distribution of the keffS calculated by the Monte Carlo code. Application of the method to a group of benchmarks modeled using the KENO-Va code and the SCALE 27 group cross sections is also presented
Racial bias in perceptions of others' pain.
Directory of Open Access Journals (Sweden)
Sophie Trawalter
Full Text Available The present work provides evidence that people assume a priori that Blacks feel less pain than do Whites. It also demonstrates that this bias is rooted in perceptions of status and the privilege (or hardship status confers, not race per se. Archival data from the National Football League injury reports reveal that, relative to injured White players, injured Black players are deemed more likely to play in a subsequent game, possibly because people assume they feel less pain. Experiments 1-4 show that White and Black Americans-including registered nurses and nursing students-assume that Black people feel less pain than do White people. Finally, Experiments 5 and 6 provide evidence that this bias is rooted in perceptions of status, not race per se. Taken together, these data have important implications for understanding race-related biases and healthcare disparities.
Observational biases in flux magnification measurements
Hildebrandt, Hendrik
2015-01-01
Flux magnification is an interesting complement to shear-based lensing measurements, especially at high redshift where sources are harder to resolve. One measures either changes in the source density (magnification bias) or in the shape of the flux distribution (e.g. magnitude-shift). The interpretation of these measurements relies on theoretical estimates of how the observables change under magnification. Here we present simulations to create multi-band photometric mock catalogues of Lyman-break galaxies in a CFHTLenS-like survey that include several observational effects that can change these relations, making simple theoretical estimates unusable. In particular, we show how the magnification bias can be affected by photometric noise, colour selection, and dust extinction. We find that a simple measurement of the slope of the number-counts is not sufficient for the precise interpretation of virtually all observations of magnification bias. We also explore how sensitive the shift in the mean magnitude of a s...
Linearity Limits of Biased 1337 Trap Detectors
Balling, Petr
2015-01-01
The upper power limit of linear response of light trap detectors was recently measured [2,3]. We have completed this measurement with test of traps with bias voltage at several visible wavelengths using silicon photodiodes Hamamatsu S1337 1010 and made a brief test of S5227 1010. Bias extends the linearity limit by factor of more than 10 for very narrow beams and more than 30 for wide beams [5]. No irreversible changes were detected even for the highest irradiance of 33 W/cm2 at 406nm. Here we present measurement of minimal bias voltage necessary for 99%, 99.8% and 99.95% linearity for several beam sizes.
Improved detection in CDMA for biased sources
Energy Technology Data Exchange (ETDEWEB)
Efraim, Hadar [Minerva Center and Department of Physics, Bar-Ilan University, Ramat-Gan 52900 (Israel); Yacov, Nadav [Minerva Center and Department of Physics, Bar-Ilan University, Ramat-Gan 52900 (Israel); Shental, Ori [Center for Magnetic Recording Research (CMRR), University of California, San Diego (UCSD), 9500 Gilman Drive, La Jolla, CA 92093 (United States); Kanter, Ido [Minerva Center and Department of Physics, Bar-Ilan University, Ramat-Gan 52900 (Israel); Saad, David [Neural Computing Research Group, Aston University, Birmingham B4 7ET (United Kingdom)
2007-08-17
We consider the detection of biased information sources in the ubiquitous code-division multiple-access (CDMA) scheme. We propose a simple modification to both the popular single-user matched-filter detector and a recently introduced near-optimal message-passing-based multiuser detector. This modification allows for detecting modulated biased sources directly with no need for source coding. Analytical results and simulations with excellent agreement are provided, demonstrating substantial improvement in bit error rate in comparison with the unmodified detectors and the alternative of source compression. The robustness of error-performance improvement is shown under practical model settings, including bias estimation mismatch and finite-length spreading codes.
Improved detection in CDMA for biased sources
International Nuclear Information System (INIS)
We consider the detection of biased information sources in the ubiquitous code-division multiple-access (CDMA) scheme. We propose a simple modification to both the popular single-user matched-filter detector and a recently introduced near-optimal message-passing-based multiuser detector. This modification allows for detecting modulated biased sources directly with no need for source coding. Analytical results and simulations with excellent agreement are provided, demonstrating substantial improvement in bit error rate in comparison with the unmodified detectors and the alternative of source compression. The robustness of error-performance improvement is shown under practical model settings, including bias estimation mismatch and finite-length spreading codes
Zero-Variance Zero-Bias Principle for Observables in quantum Monte Carlo: Application to Forces
Assaraf, R
2003-01-01
A simple and stable method for computing accurate expectation values of observable with Variational Monte Carlo (VMC) or Diffusion Monte Carlo (DMC) algorithms is presented. The basic idea consists in replacing the usual ``bare'' estimator associated with the observable by an improved or ``renormalized'' estimator. Using this estimator more accurate averages are obtained: Not only the statistical fluctuations are reduced but also the systematic error (bias) associated with the approximate VMC or (fixed-node) DMC probability densities. It is shown that improved estimators obey a Zero-Variance Zero-Bias (ZVZB) property similar to the usual Zero-Variance Zero-Bias property of the energy with the local energy as improved estimator. Using this property improved estimators can be optimized and the resulting accuracy on expectation values may reach the remarkable accuracy obtained for total energies. As an important example, we present the application of our formalism to the computation of forces in molecular system...
Directory of Open Access Journals (Sweden)
Mahmood Yahyazadehfar
2012-11-01
Full Text Available The purpose of this study is investigating the Status Quo Bias (SQB from suggested biases in behavioral finance. People who are subject to a SQB tend to choose an alternative that was chosen previously (i.e., their status quo even if it is not the optimal choice any more. Status quo bias existence was investigated in this study using Ruenzi and Kempf (2005 model among investment companies listed in Tehran's Stock Exchange during 2003-2010. The data is collected quarterly from investment companies. Also, Stata10.0 software package is used for statistical analysis. The result shows the existence of a SQB is not found in Tehran Stock Exchange
Relative Age Effect in Elite Sports: Methodological Bias or Real Discrimination?
Delorme, Nicolas; Raspaud, Michel; 10.1080/17461390903271584
2010-01-01
Sport sciences researchers talk about a relative age effect when they observe a biased distribution of elite athletes' birthdates, with an over-representation of those born at the beginning of the competitive year and an under-representation of those born at the end. Using the whole sample of the French male licensed soccer players (n = 1,831,524), our study suggests that there could be an important bias in the statistical test of this effect. This bias could in turn lead to falsely conclude to a systemic discrimination in the recruitment of professional players. Our findings question the accuracy of past results concerning the existence of this effect at the elite level.
Over-bias Light Emission due to Higher Order Quantum Noise of a Tunnel Junction
Belzig, Wolfgang; Xu, Fei; Holmqvist, Cecilia
Understanding tunneling from an atomically sharp tip to a metallic surface requires to account for interactions on a nanoscopic scale. Inelastic tunneling of electrons generates emission of photons, whose energies intuitively should be limited by the applied bias voltage. However, experiments indicate that more complex processes involving the interaction of electrons with plasmon polaritons lead to photon emission characterized by over-bias energies. We propose a model of this observation in analogy to the dynamical Coulomb blockade, originally developed for treating the electronic environment in mesoscopic circuits. We explain the experimental finding quantitatively by the correlated tunneling of two electrons interacting with an LRC circuit modeling the local plasmon-polariton mode. To explain the over-bias emission, the non-Gaussian statistics of the tunneling dynamics of the electrons is essential.
Directory of Open Access Journals (Sweden)
Adam Zaremba
2011-07-01
Full Text Available Managed futures are an alternative asset class which has recently became considerably popular among investment industry. However, due to its characteristics, access to managed futures historical performance statistics is relatively confined. All available information originates from commercial and academic databases, reporting to which is entirely voluntary. This situation results in series of biases which distort the managed futures performance in the eyes of investors. The paper consists of two parts. First, the author reviews and describes various biases that influence the reliability of the managed futures indices and databases. The second section encompasses author’s proposals of potential enhancements, which aim to reduce the impact of the biases in order to derive a benchmark that could better reflect characteristics of managed futures investment from the point of view of a potential investor.
Williams, Paige; Kern, Margaret L; Waters, Lea
2016-01-01
Employee psychological capital (PsyCap), perceptions of organizational virtue (OV), and work happiness have been shown to be associated within and over time. This study examines selective exposure and confirmation bias as potential processes underlying PsyCap, OV, and work happiness associations. As part of a quasi-experimental study design, school staff (N = 69) completed surveys at three time points. After the first assessment, some staff (n = 51) completed a positive psychology training intervention. Results of descriptive statistics, correlation, and regression analyses on the intervention group provide some support for selective exposure and confirmation bias as explanatory mechanisms. In focusing on the processes through which employee attitudes may influence work happiness this study advances theoretical understanding, specifically of selective exposure and confirmation bias in a field study context. PMID:27378978
Maurer, E. P.; Ficklin, D. L.; Wang, W.
2016-02-01
Statistical downscaling is a commonly used technique for translating large-scale climate model output to a scale appropriate for assessing impacts. To ensure downscaled meteorology can be used in climate impact studies, downscaling must correct biases in the large-scale signal. A simple and generally effective method for accommodating systematic biases in large-scale model output is quantile mapping, which has been applied to many variables and shown to reduce biases on average, even in the presence of non-stationarity. Quantile-mapping bias correction has been applied at spatial scales ranging from hundreds of kilometers to individual points, such as weather station locations. Since water resources and other models used to simulate climate impacts are sensitive to biases in input meteorology, there is a motivation to apply bias correction at a scale fine enough that the downscaled data closely resemble historically observed data, though past work has identified undesirable consequences to applying quantile mapping at too fine a scale. This study explores the role of the spatial scale at which the quantile-mapping bias correction is applied, in the context of estimating high and low daily streamflows across the western United States. We vary the spatial scale at which quantile-mapping bias correction is performed from 2° ( ˜ 200 km) to 1/8° ( ˜ 12 km) within a statistical downscaling procedure, and use the downscaled daily precipitation and temperature to drive a hydrology model. We find that little additional benefit is obtained, and some skill is degraded, when using quantile mapping at scales finer than approximately 0.5° ( ˜ 50 km). This can provide guidance to those applying the quantile-mapping bias correction method for hydrologic impacts analysis.
Bangladesh; Statistical Appendix
International Monetary Fund
1995-01-01
The paper presents statistical data on gross domestic product, agricultural production, manufacturing production, energy statistics, retail prices of petroleum products, consumer price index, central government operations, revenues, and central expenditure in Bangladesh. It also presents the central government food account, consolidated accounts and profits of nonfinancial public enterprises, government domestic securities, monetary survey, balance sheet of the monetary authorities, interest ...
Handbook of Spatial Statistics
Gelfand, Alan E
2010-01-01
Offers an introduction detailing the evolution of the field of spatial statistics. This title focuses on the three main branches of spatial statistics: continuous spatial variation (point referenced data); discrete spatial variation, including lattice and areal unit data; and, spatial point patterns.
DEFF Research Database (Denmark)
Lauritzen, Steffen Lilholt
This book studies the brilliant Danish 19th Century astronomer, T.N. Thiele who made important contributions to statistics, actuarial science, astronomy and mathematics. The most important of these contributions in statistics are translated into English for the first time, and the text includes...
Statistical Hadronization and Holography
DEFF Research Database (Denmark)
Bechi, Jacopo
2009-01-01
In this paper we consider some issues about the statistical model of the hadronization in a holographic approach. We introduce a Rindler like horizon in the bulk and we understand the string breaking as a tunneling event under this horizon. We calculate the hadron spectrum and we get a thermal, and...... so statistical, shape for it....
Statistical parametric mapping (SPM)
Flandin, G.; Friston, K.J.
2008-01-01
Statistical parametric mapping is the application of Random Field Theory to make inferences about the topological features of statistical processes that are continuous functions of space or time. It is usually used to identify regionally specific effects (e.g., brain activations) in neuroimaging data to characterize functional anatomy and disease-related changes.
The purpose of the Disability Statistics Center is to produce and disseminate statistical information on disability and the status of people with disabilities in American society and to establish and monitor indicators of how conditions are changing over time to meet their health...
Statistics 101 for Radiologists.
Anvari, Arash; Halpern, Elkan F; Samir, Anthony E
2015-10-01
Diagnostic tests have wide clinical applications, including screening, diagnosis, measuring treatment effect, and determining prognosis. Interpreting diagnostic test results requires an understanding of key statistical concepts used to evaluate test efficacy. This review explains descriptive statistics and discusses probability, including mutually exclusive and independent events and conditional probability. In the inferential statistics section, a statistical perspective on study design is provided, together with an explanation of how to select appropriate statistical tests. Key concepts in recruiting study samples are discussed, including representativeness and random sampling. Variable types are defined, including predictor, outcome, and covariate variables, and the relationship of these variables to one another. In the hypothesis testing section, we explain how to determine if observed differences between groups are likely to be due to chance. We explain type I and II errors, statistical significance, and study power, followed by an explanation of effect sizes and how confidence intervals can be used to generalize observed effect sizes to the larger population. Statistical tests are explained in four categories: t tests and analysis of variance, proportion analysis tests, nonparametric tests, and regression techniques. We discuss sensitivity, specificity, accuracy, receiver operating characteristic analysis, and likelihood ratios. Measures of reliability and agreement, including κ statistics, intraclass correlation coefficients, and Bland-Altman graphs and analysis, are introduced. PMID:26466186
Introduction to BIS statistics
Bank for International Settlements
2015-01-01
The BIS has expanded its statistics by publishing additional data, revamping their dissemination and strengthening their policy orientation. This special feature, prepared by members of the BIS Monetary and Economic Department, briefly describes each BIS data set and explains how the statistics can be used for analysis.
Statistical Mapping by Computer.
Utano, Jack J.
The function of a statistical map is to provide readers with a visual impression of the data so that they may be able to identify any geographic characteristics of the displayed phenomena. The increasingly important role played by the computer in the production of statistical maps is manifested by the varied examples of computer maps in recent…
Statistical Engine Knock Control
DEFF Research Database (Denmark)
Stotsky, Alexander A.
2008-01-01
A new statistical concept of the knock control of a spark ignition automotive engine is proposed . The control aim is associated with the statistical hy pothesis test which compares the threshold value to the average value of the max imal amplitud e of the knock sensor signal at a given freq uency...
Practical statistics for educators
Ravid, Ruth
2014-01-01
Practical Statistics for Educators, Fifth Edition, is a clear and easy-to-follow text written specifically for education students in introductory statistics courses and in action research courses. It is also a valuable resource and guidebook for educational practitioners who wish to study their own settings.
Practical statistics simply explained
Langley, Dr Russell A
1971-01-01
For those who need to know statistics but shy away from math, this book teaches how to extract truth and draw valid conclusions from numerical data using logic and the philosophy of statistics rather than complex formulae. Lucid discussion of averages and scatter, investigation design, more. Problems with solutions.
Huizingh, Eelko K. R. E.
2007-01-01
Accessibly written and easy to use, "Applied Statistics Using SPSS" is an all-in-one self-study guide to SPSS and do-it-yourself guide to statistics. What is unique about Eelko Huizingh's approach is that this book is based around the needs of undergraduate students embarking on their own research project, and its self-help style is designed to…
Cancer Data and Statistics Tools
... in Cancer Moonshot Stay Informed Cancer Data and Statistics Tools Recommend on Facebook Tweet Share Compartir United States Cancer Statistics The United States Cancer Statistics (USCS): Incidence and ...
Traders, Courts and the Home Bias Puzzle
Turrini, Alessandro; Van Ypersele, Tanguy
2001-01-01
Recent evidence shows that the ‘home bias puzzle’ in international trade may be associated with the mere presence of national borders (McCallum (1995)). In this Paper we provide a theoretical framework to explain why borders may matter so much for trade. Our argument is that even between perfectly integrated and similar countries the legal system differs, so that legal costs are higher when business is done abroad. Using a matching model of trade, we show that the home bias is associated with...
Motion, identity and the bias toward agency
Chris Fields
2014-01-01
The well-documented human bias toward agency as a cause and therefore an explanation of observed events is typically attributed to evolutionary selection for a “social brain.” Based on a review of developmental and adult behavioral and neurocognitive data, it is argued that the bias toward agency is a result of the default human solution, developed during infancy, to the computational requirements of object re-identification over gaps in observation of more than a few seconds. If this model...
Motion, identity and the bias toward agency
Fields, Chris
2014-01-01
The well-documented human bias toward agency as a cause and therefore an explanation of observed events is typically attributed to evolutionary selection for a “social brain”. Based on a review of developmental and adult behavioral and neurocognitive data, it is argued that the bias toward agency is a result of the default human solution, developed during infancy, to the computational requirements of object re-identification over gaps in observation of more than a few seconds. If this model i...
BIAS GENDER: MASALAH UTAMA DALAM INTERPRETASI ARKEOLOGI
Directory of Open Access Journals (Sweden)
Mimi Savitri
2007-06-01
Full Text Available Gender bias is an important theme in Gender Archaeology. It is influenced by modern people thinking and it has influenced archaeological interpretation for a long time. As a result, archaeological interpretation of past society is not objective. This problem should be solved to reach an objective interpretation of people’s life in the past. The author argues that gender bias in archaeology can be solved by actively criticizing androcentrism and paying more attention to men and women’s relationship in the past.
Optimal design of APD biasing circuit
Institute of Scientific and Technical Information of China (English)
SUN Chun-sheng; QIN Shi-qiao; WANG Xing-shu; ZHU Dong-hua
2007-01-01
This paper proposes a control method for avalanche photodiode (APD) reverse bias with temperature compensation and load resistance compensation. The influence of background light and load resistance on APD detection circuit is analyzed in detail. A theoretical model of temperature compensation and load resistance compensation is established, which is used for APD biasing circuit designing. It is predicted that this control method is especially suitable for LD laser range finder used on vehicles. Experimental results confirm thatthe design proposed in this paper can considerablely improve the performance of range finder.
Statistical Methods for Astronomy
Feigelson, Eric D
2012-01-01
This review outlines concepts of mathematical statistics, elements of probability theory, hypothesis tests and point estimation for use in the analysis of modern astronomical data. Least squares, maximum likelihood, and Bayesian approaches to statistical inference are treated. Resampling methods, particularly the bootstrap, provide valuable procedures when distributions functions of statistics are not known. Several approaches to model selection and good- ness of fit are considered. Applied statistics relevant to astronomical research are briefly discussed: nonparametric methods for use when little is known about the behavior of the astronomical populations or processes; data smoothing with kernel density estimation and nonparametric regression; unsupervised clustering and supervised classification procedures for multivariate problems; survival analysis for astronomical datasets with nondetections; time- and frequency-domain times series analysis for light curves; and spatial statistics to interpret the spati...
Geometrisation of Statistical Mechanics
Brody, D C; Brody, Dorje C.; Hughston, Lane P.
1997-01-01
Classical and quantum statistical mechanics are cast here in the language of projective geometry to provide a unified geometrical framework for statistical physics. After reviewing the Hilbert space formulation of classical statistical thermodynamics, we introduce projective geometry as a basis for analysing probabilistic aspects of statistical physics. In particular, the specification of a canonical polarity on $RP^{n}$ induces a Riemannian metric on the state space of statistical mechanics. In the case of the canonical ensemble, we show that equilibrium thermal states are determined by the Hamiltonian gradient flow with respect to this metric. This flow is concisely characterised by the fact that it induces a projective automorphism on the state manifold. The measurement problem for thermal systems is studied by the introduction of the concept of a random state. The general methodology is then extended to include the quantum mechanical dynamics of equilibrium thermal states. In this case the relevant state ...
Statistical laws in linguistics
Altmann, Eduardo G
2015-01-01
Zipf's law is just one out of many universal laws proposed to describe statistical regularities in language. Here we review and critically discuss how these laws can be statistically interpreted, fitted, and tested (falsified). The modern availability of large databases of written text allows for tests with an unprecedent statistical accuracy and also a characterization of the fluctuations around the typical behavior. We find that fluctuations are usually much larger than expected based on simplifying statistical assumptions (e.g., independence and lack of correlations between observations).These simplifications appear also in usual statistical tests so that the large fluctuations can be erroneously interpreted as a falsification of the law. Instead, here we argue that linguistic laws are only meaningful (falsifiable) if accompanied by a model for which the fluctuations can be computed (e.g., a generative model of the text). The large fluctuations we report show that the constraints imposed by linguistic laws...
Statistical downscaling using K-nearest neighbors
Gangopadhyay, Subhrendu; Clark, Martyn; Rajagopalan, Balaji
2005-02-01
Statistical downscaling provides a technique for deriving local-scale information of precipitation and temperature from numerical weather prediction model output. The K-nearest neighbor (K-nn) is a new analog-type approach that is used in this paper to downscale the National Centers for Environmental Prediction 1998 medium-range forecast model output. The K-nn algorithm queries days similar to a given feature vector in this archive and using empirical orthogonal function analysis identifies a subset of days (K) similar to the feature day. These K days are then weighted using a bisquare weight function and randomly sampled to generate ensembles. A set of 15 medium-range forecast runs was used, and seven ensemble members were generated from each run. The ensemble of 105 members was then used to select the local-scale precipitation and temperature values in four diverse basins across the contiguous United States. These downscaled precipitation and temperature estimates were subsequently analyzed to test the performance of this downscaling approach. The downscaled ensembles were evaluated in terms of bias, the ranked probability skill score as a measure of forecast skill, spatial covariability between stations, temporal persistence, consistency between variables, and conditional bias and to develop spread-skill relationships. Though this approach does not explicitly model the space-time variability of the weather fields at each individual station, the above statistics were extremely well captured. The K-nn method was also compared with a multiple-linear-regression-based downscaling model.
Attention Bias Variability and Symptoms of Posttraumatic Stress Disorder
Iacoviello, Brian M.; Wu, Gang; Abend, Rany; Murrough, James W.; Feder, Adriana; Fruchter, Eyal; Levinstein, Yoav; Wald, Ilan; Bailey, Christopher R.; Pine, Daniel S.; Neumeister, Alexander; Bar-Haim, Yair; Charney, Dennis S.
2014-01-01
Cognitive theories implicate information-processing biases in the etiology of anxiety disorders. Results of attention-bias studies in posttraumatic stress disorder (PTSD) have been inconsistent, suggesting biases towards and away from threat. Within-subject variability of attention biases in posttraumatic patients may be a useful marker for attentional control impairment and the development of posttrauma symptoms. This study reports 2 experiments investigating threat-related attention biases,...
The influence of cognitive biases on psychophysiological vulnerability to stress
Randall, Kate
2012-01-01
Individuals who disproportionately attend to negative aspects of a situation (attention bias), or who unduly interpret ambiguity in a negative manner (interpretive bias) report more psychological ill-effects of stress than those with balanced or positively-skewed inclinations. Cognitive Bias Modification (CBM) techniques improve maladaptive biases through implicitly-based association learning, with induced positive biases buffering the future perception of stress. Six experimen...
Information bias in health research: definition, pitfalls, and adjustment methods
Althubaiti, Alaa
2016-01-01
As with other fields, medical sciences are subject to different sources of bias. While understanding sources of bias is a key element for drawing valid conclusions, bias in health research continues to be a very sensitive issue that can affect the focus and outcome of investigations. Information bias, otherwise known as misclassification, is one of the most common sources of bias that affects the validity of health research. It originates from the approach that is utilized to obtain or confir...
Godleski, Stephanie A.; Ostrov, Jamie M.
2010-01-01
The present study used both categorical and dimensional approaches to test the association between relational and physical aggression and hostile intent attributions for both relational and instrumental provocation situations using the National Institute of Child Health and Human Development longitudinal Study of Early Child Care and Youth…
Gaussian statistics for palaeomagnetic vectors
Love, J.J.; Constable, C.G.
2003-01-01
With the aim of treating the statistics of palaeomagnetic directions and intensities jointly and consistently, we represent the mean and the variance of palaeomagnetic vectors, at a particular site and of a particular polarity, by a probability density function in a Cartesian three-space of orthogonal magnetic-field components consisting of a single (unimoda) non-zero mean, spherically-symmetrical (isotropic) Gaussian function. For palaeomagnetic data of mixed polarities, we consider a bimodal distribution consisting of a pair of such symmetrical Gaussian functions, with equal, but opposite, means and equal variances. For both the Gaussian and bi-Gaussian distributions, and in the spherical three-space of intensity, inclination, and declination, we obtain analytical expressions for the marginal density functions, the cumulative distributions, and the expected values and variances for each spherical coordinate (including the angle with respect to the axis of symmetry of the distributions). The mathematical expressions for the intensity and off-axis angle are closed-form and especially manageable, with the intensity distribution being Rayleigh-Rician. In the limit of small relative vectorial dispersion, the Gaussian (bi-Gaussian) directional distribution approaches a Fisher (Bingham) distribution and the intensity distribution approaches a normal distribution. In the opposite limit of large relative vectorial dispersion, the directional distributions approach a spherically-uniform distribution and the intensity distribution approaches a Maxwell distribution. We quantify biases in estimating the properties of the vector field resulting from the use of simple arithmetic averages, such as estimates of the intensity or the inclination of the mean vector, or the variances of these quantities. With the statistical framework developed here and using the maximum-likelihood method, which gives unbiased estimates in the limit of large data numbers, we demonstrate how to
The Specific Bias in Dynamic Monte Carlo Simulations of Nuclear Reactor
Yamamoto, Toshihisa; Endo, Hiroshi; Ishizu, Tomoko; Tatewaki, Isao
2014-06-01
During the development of Monte-Carlo-based dynamic code system, we have encountered two major Monte-Carlo-specific problems. One is the break down due to "false super-criticality" which is caused by an accidentally large eigenvalue due to statistical error in spite of the fact that the reactor is actually not. The other problem, which is the main topic in this paper, is that the statistical error in power level using the reactivity calculated with Monte Carlo code is not symmetric about its mean but always positively biased. This signifies that the bias is accumulated as the calculation proceeds and consequently results in over-estimation of the final power level. It should be noted that the bias will not eliminated by refining time step as long as the variance is not zero. A preliminary investigation on this matter using the one-group-precursor point kinetic equations was made and it was concluded that the bias in power level is approximately proportional to the product of variance in Monte Carlo calculation and elapsed time. This conclusion was verified with some numerical experiments. This outcome is important in quantifying the required precision of the Monte-Carlo-based reactivity calculations.
Directory of Open Access Journals (Sweden)
Alexander Miloff
2015-09-01
Full Text Available Social anxiety disorder (SAD and attentional bias are theoretically connected in cognitive behavioral therapeutic models. In fact, there is an emerging field focusing on modifying attentional bias as a stand-alone treatment. However, it is unclear to what degree these attentional biases are present before commencing treatment. The purpose of this study was to measure pre-treatment attentional bias in 153 participants diagnosed with SAD using a home-based Internet version of the dot-probe paradigm. Results showed no significant correlation for attentional bias (towards or away from negative words or faces and the self-rated version of the Liebowitz Social Anxiety Scale (LSAS-SR. However, two positive correlations were found for the secondary measures Generalized Anxiety Disorder 7 (GAD-7 and Patient Health Questionnaire 9 (PHQ-9. These indicated that those with elevated levels of anxiety and depression had a higher bias towards negative faces in neutral–negative and positive–negative valence combinations, respectively. The unreliability of the dot-probe paradigm and home-based Internet delivery are discussed to explain the lack of correlations between LSAS-SR and attentional bias. Changes to the dot-probe task are suggested that could improve reliability.
UN Data- Environmental Statistics: Waste
World Wide Human Geography Data Working Group — The Environment Statistics Database contains selected water and waste statistics by country. Statistics on water and waste are based on official statistics supplied...
UN Data: Environment Statistics: Waste
World Wide Human Geography Data Working Group — The Environment Statistics Database contains selected water and waste statistics by country. Statistics on water and waste are based on official statistics supplied...
Creating Culturally Considerate Schools: Educating without Bias
Anderson, Kim L.; Davis, Bonnie M.
2012-01-01
This unique collaboration between a veteran educator and a psychotherapist shows that the educators who are most effective in teaching diverse student populations are the ones who can "see students clearly and respond to their needs without hesitation or bias." Framed around an original, eight-stage model of diversity development, this book…
Avoiding bias in safety testing design
DEFF Research Database (Denmark)
Calow, Peter
2011-01-01
All scientists are biased, no matter what their backgrounds or affiliations, so what is it about the scientific method that overcomes this and which makes science so successful? Key features are transparency and critical peer scrutiny. These general issues will be will be considered in terms...
Exchange bias mediated by interfacial nanoparticles (invited)
Energy Technology Data Exchange (ETDEWEB)
Berkowitz, A. E., E-mail: aberk@ucsd.edu [Department of Physics, University of California, San Diego, La Jolla, California 92093 (United States); Center for Magnetic Recording Research, University of California, California 92093 (United States); Sinha, S. K. [Department of Physics, University of California, San Diego, La Jolla, California 92093 (United States); Fullerton, E. E. [Center for Magnetic Recording Research, University of California, California 92093 (United States); Smith, D. J. [Department of Physics, Arizona State University, Tempe, Arizona 85287 (United States)
2015-05-07
The objective of this study on the iconic exchange-bias bilayer Permalloy/CoO has been to identify those elements of the interfacial microstructure and accompanying magnetic properties that are responsible for the exchange-bias and hysteretic properties of this bilayer. Both epitaxial and polycrystalline samples were examined. X-ray and neutron reflectometry established that there existed an interfacial region, of width ∼1 nm, whose magnetic properties differed from those of Py or CoO. A model was developed for the interfacial microstructure that predicts all the relevant properties of this system; namely; the temperature and Permalloy thickness dependence of the exchange-bias, H{sub EX}, and coercivity, H{sub C}; the much smaller measured values of H{sub EX} from what was nominally expected; the different behavior of H{sub EX} and H{sub C} in epitaxial and polycrystalline bilayers. A surprising result is that the exchange-bias does not involve direct exchange-coupling between Permalloy and CoO, but rather is mediated by CoFe{sub 2}O{sub 4} nanoparticles in the interfacial region.
A new polarization amplitude bias reduction method
Vidal, Matias; Leahy, J. P.; Dickinson, C.
2016-09-01
Polarization amplitude estimation is affected by a positive noise bias, particularly important in regions with low signal-to-noise ratio (SNR). We present a new approach to correct for this bias in the case there is additional information about the polarization angle. We develop the `known-angle estimator' that works in the special case when there is an independent and high SNR (≳ 2σ) measurement of the polarization angle. It is derived for the general case where the uncertainties in the Q, U Stokes parameters are not symmetric. This estimator completely corrects for the polarization bias if the polarization angle is perfectly known. In the realistic case, where the angle template has uncertainties, a small residual bias remains, but that is shown to be much smaller that the one left by other classical estimators. We also test our method with more realistic data, using the noise properties of the three lower frequency maps of Wilkinson Microwave Anisotropy Probe. In this case, the known-angle estimator also produces better results than methods that do not include the angle information. This estimator is therefore useful in the case where the polarization angle is expected to be constant over different data sets with different SNR.
Clustering and Bias Measurements of SDSS Voids
Clampitt, Joseph; Sánchez, Carles
2015-01-01
Using a void catalog from the SDSS survey, we present the first measurements of void clustering and the corresponding void bias. Over the range 30-200 Mpc/h the void auto-correlation is detected at 5-sigma significance for voids of radius 15-20 Mpc/h. We also measure the void-galaxy cross-correlation at higher signal-to-noise and compare the inferred void bias with the autocorrelation results. Void bias is constant with scale for voids of a given size, but its value falls from 5.6 +/- 1.0 to below zero as the void radius increases from 15 to 30 Mpc/h. The comparison of our measurements with carefully matched galaxy mock catalogs, with no free parameters related to the voids, shows that model predictions can be reliably made for void correlations. We study the dependence of void bias on tracer density and void size with a view to future applications. In combination with our previous lensing measurements of void mass profiles, these clustering measurements provide another step towards using voids as cosmologica...
Uncovering Racial Bias in Nursing Fundamentals Textbooks.
Byrne, Michelle M.
2001-01-01
The portrayal of African Americans in nursing fundamentals textbooks was analyzed, resulting in 11 themes in the areas of history, culture, and physical assessment. Few African American leaders were included, and racial bias and stereotyping were apparent. Differences were often discussed using Eurocentric norms, and language tended to minimize…
Bounding the Bias of Contrastive Divergence Learning
DEFF Research Database (Denmark)
Fischer, Anja; Igel, Christian
2011-01-01
number of variables in the RBM, and the maximum change in energy that can be produced by changing a single variable. The last reflects the dependence on the absolute values of the RBM parameters. The magnitude of the bias is also affected by the distance in variation between the modeled distribution and...
Examining Gender Bias in Studies of Innovation
Crowden, N.
2003-01-01
This paper examines the presence of a gender bias in studies of innovation. Using the Innovation Systems Research Network (ISRN) and its interview guide as a case study, this research project examines how accurately and completely such innovation studies present gender differences in the innovation process.
Zero bias transformation and asymptotic expansions
Jiao, Ying
2012-01-01
Let W be a sum of independent random variables. We apply the zero bias transformation to deduce recursive asymptotic expansions for $\\mathbb {E}[h(W)]$ in terms of normal expectations, or of Poisson expectations for integer-valued random variables. We also discuss the estimates of remaining errors.
Knowledge of Social Affiliations Biases Economic Decisions
Martinez, Joel E.; Mack, Michael L.; Gelman, Bernard D.; Preston, Alison R.
2016-01-01
An individual’s reputation and group membership can produce automatic judgments and behaviors toward that individual. Whether an individual’s social reputation impacts interactions with affiliates has yet to be demonstrated. We tested the hypothesis that during initial encounters with others, existing knowledge of their social network guides behavior toward them. Participants learned reputations (cooperate, defect, or equal mix) for virtual players through an iterated economic game (EG). Then, participants learned one novel friend for each player. The critical question was how participants treated the friends in a single-shot EG after the friend-learning phase. Participants tended to cooperate with friends of cooperators and defect on friends of defectors, indicative of a decision making bias based on memory for social affiliations. Interestingly, participants’ explicit predictions of the friends’ future behavior showed no such bias. Moreover, the bias to defect on friends of defectors was enhanced when affiliations were learned in a social context; participants who learned to associate novel faces with player faces during reinforcement learning did not show reputation-based bias for associates of defectors during single-shot EG. These data indicate that when faced with risky social decisions, memories of social connections influence behavior implicitly. PMID:27441563
Assessing Projection Bias in Consumers' Food Preferences.
de-Magistris, Tiziana; Gracia, Azucena
2016-01-01
The aim of this study is to test whether projection bias exists in consumers' purchasing decisions for food products. To achieve our aim, we used a non-hypothetical experiment (i.e., experimental auction), where hungry and non-hungry participants were incentivized to reveal their willingness to pay (WTP). The results confirm the existence of projection bias when consumers made their decisions on food products. In particular, projection bias existed because currently hungry participants were willing to pay a higher price premium for cheeses than satiated ones, both in hungry and satiated future states. Moreover, participants overvalued the food product more when they were delivered in the future hungry condition than in the satiated one. Our study provides clear, quantitative and meaningful evidence of projection bias because our findings are based on economic valuation of food preferences. Indeed, the strength of this study is that findings are expressed in terms of willingness to pay which is an interpretable amount of money. PMID:26828930
Assessing Projection Bias in Consumers’ Food Preferences
de-Magistris, Tiziana; Gracia, Azucena
2016-01-01
The aim of this study is to test whether projection bias exists in consumers’ purchasing decisions for food products. To achieve our aim, we used a non-hypothetical experiment (i.e., experimental auction), where hungry and non-hungry participants were incentivized to reveal their willingness to pay (WTP). The results confirm the existence of projection bias when consumers made their decisions on food products. In particular, projection bias existed because currently hungry participants were willing to pay a higher price premium for cheeses than satiated ones, both in hungry and satiated future states. Moreover, participants overvalued the food product more when they were delivered in the future hungry condition than in the satiated one. Our study provides clear, quantitative and meaningful evidence of projection bias because our findings are based on economic valuation of food preferences. Indeed, the strength of this study is that findings are expressed in terms of willingness to pay which is an interpretable amount of money. PMID:26828930
Exchange bias of conetic thin films
Eggers, Tatiana; Kirby, Hillary; Jayathilaka, Priyanga; Campbell, Scott; Miller, Casey
2012-02-01
In this work, we study the exchange bias and coercivity of Ni77Fe14Cu5Mo4 (Conetic, also known as mu-metal) exchange coupled with FeMn as functions of Conetic thickness and buffer layer material. The samples studied were BL(30nm)/Conetic(9nm-30nm)/FeMn(10nm)/Ta(5nm), where BL = Cu or Ta. All samples were grown by magnetron sputtering in a deposition field of ˜150 Oe during growth to set the exchange bias axis. Room temperature hysteresis loops were measured by a magneto-optical Kerr effect magnetometer as a function of applied-field angle. For each variety of sample, the exchange bias and coercivity were inversely proportional to Conetic thickness. With Cu buffer layers grown on Si, the Heb decreased from 300 Oe to 62 Oe, and Hc decreased from 99 Oe to 9 Oe. Similar results were found when the Cu buffer layer was grown on SiOx, though the maximum coercivity was only 67 Oe. For the samples grown on Si(001)/Ta(5nm), the exchange bias decreased from 80 Oe to 14 Oe, while the coercivity increases only slightly from 2 Oe to 10 Oe. These results indicate a trade-off between preserving the softness of the ferromagnet and having a large exchange, which may be useful for tuning the performance of low-field sensing materials
Researching Sex Bias in the Classroom.
Donlan, Dan
This paper outlines five methods of research on sex bias in the classroom: one-time survey, one class/one treatment, two class/two treatment, one class/random assignment to treatment, and analysis of differentiated effect. It shows how each method could be used in attempting to measure the effect of a unit on Norma Klein's "Mom, the Wolfman and…
Linguistic Abstractness, Intergroup Bias and National Essentialism
Czech Academy of Sciences Publication Activity Database
Kouřilová, Sylvie; Geschke, D.; Finell, E.; Bilewicz, M.; Casini, A.
2007, s. 25-25. [Transfer of Knowledge Conference. Brno (CZ), 05.09.2007-09.09.2007] R&D Projects: GA ČR GA406/07/1561 Institutional research plan: CEZ:AV0Z70250504 Keywords : language abstraction * linguistic category model * intergroup bias, national essentialism Subject RIV: AN - Psychology
Bias sensitive multispectral structures for imaging applications
International Nuclear Information System (INIS)
In this paper we present results on the optimization of an pinpii'n' type a-Si:H based three color detector with voltage controlled spectral sensitivity. The sensor element was fabricated on a glass covered with Indium Tin Oxide (ITO) and consists of a p-i-n a-SiC:H multilayer structure which faces the incident illumination, followed by a-SiC:H(-p)/a-SiC:H(-i)/a-Si:H(-i')/a-SiC:H(-n')/ITO heterostructure, that allows the optically addressed readout. Results show that this approach leads to regionally different collection parameters resulting in multispectral photodiodes. In the polychromatic operation mode different sensitivity ranges are programmed by switching between different biases so that the basic colors can be resolved with a single device. Positive bias is needed under blue irradiation and moderated reverse bias under green. The threshold voltage between green and red sensitivity depends on the thickness of the bottom a-SiC:H (-i) layer, and corresponds to the complete confinement of the absorbed green photons across the pinpi sequence. As the thickness of the a-Si:H i'-layer increases, the self-reverse effect due to the front absorption will be balanced by the decrease of the self-forward effect due to the back absorption shifting the threshold voltage to lower reverse bias. The various design parameters are discussed and supported by a 2D numerical simulation
Teaching EFL Students about Language Bias
Randolph, Justus J.
2005-01-01
In this article, I discuss a method for teaching EFL students about language bias. The method involves (A) introducing vocabulary, (B) activating knowledge, (C) giving instruction, (D) group and individual practice, and (E) reflection. I also summarize guidelines for teaching students about the use of gendered pronouns, gender-loaded nouns and…
Very Massive Tracers and Higher Derivative Biases
Fujita, Tomohiro; Senatore, Leonardo; Vlah, Zvonimir; Angulo, Raul
2016-01-01
Most of the upcoming cosmological information will come from analyzing the clustering of the Large Scale Structures (LSS) of the universe through LSS or CMB observations. It is therefore essential to be able to understand their behavior with exquisite precision. The Effective Field Theory of Large Scale Structures (EFTofLSS) provides a consistent framework to make predictions for LSS observables in the mildly non-linear regime. In this paper we focus on biased tracers. We argue that in calculations at a given order in the dark matter perturbations, highly biased tracers will underperform because of their larger higher derivative biases. A natural prediction of the EFTofLSS is therefore that by simply adding higher derivative biases, all tracers should perform comparably well. We implement this prediction for the halo-halo and the halo-matter power spectra at one loop, and the halo-halo-halo, halo-halo-matter, and halo-matter-matter bispectra at tree-level, and compare with simulations. We find good agreement ...
Assessing Projection Bias in Consumers' Food Preferences.
Directory of Open Access Journals (Sweden)
Tiziana de-Magistris
Full Text Available The aim of this study is to test whether projection bias exists in consumers' purchasing decisions for food products. To achieve our aim, we used a non-hypothetical experiment (i.e., experimental auction, where hungry and non-hungry participants were incentivized to reveal their willingness to pay (WTP. The results confirm the existence of projection bias when consumers made their decisions on food products. In particular, projection bias existed because currently hungry participants were willing to pay a higher price premium for cheeses than satiated ones, both in hungry and satiated future states. Moreover, participants overvalued the food product more when they were delivered in the future hungry condition than in the satiated one. Our study provides clear, quantitative and meaningful evidence of projection bias because our findings are based on economic valuation of food preferences. Indeed, the strength of this study is that findings are expressed in terms of willingness to pay which is an interpretable amount of money.
Systematic Angle Random Walk Estimation of the Constant Rate Biased Ring Laser Gyro
Directory of Open Access Journals (Sweden)
Guohu Feng
2013-02-01
Full Text Available An actual account of the angle random walk (ARW coefficients of gyros in the constant rate biased rate ring laser gyro (RLG inertial navigation system (INS is very important in practical engineering applications. However, no reported experimental work has dealt with the issue of characterizing the ARW of the constant rate biased RLG in the INS. To avoid the need for high cost precise calibration tables and complex measuring set-ups, the objective of this study is to present a cost-effective experimental approach to characterize the ARW of the gyros in the constant rate biased RLG INS. In the system, turntable dynamics and other external noises would inevitably contaminate the measured RLG data, leading to the question of isolation of such disturbances. A practical observation model of the gyros in the constant rate biased RLG INS was discussed, and an experimental method based on the fast orthogonal search (FOS for the practical observation model to separate ARW error from the RLG measured data was proposed. Validity of the FOS-based method was checked by estimating the ARW coefficients of the mechanically dithered RLG under stationary and turntable rotation conditions. By utilizing the FOS-based method, the average ARW coefficient of the constant rate biased RLG in the postulate system is estimated. The experimental results show that the FOS-based method can achieve high denoising ability. This method estimate the ARW coefficients of the constant rate biased RLG in the postulate system accurately. The FOS-based method does not need precise calibration table with high cost and complex measuring set-up, and Statistical results of the tests will provide us references in engineering application of the constant rate biased RLG INS.
Watanabe, Satoshi; Kanae, Shinjiro; Seto, Shinta; Yeh, Pat J.-F.; Hirabayashi, Yukiko; Oki, Taikan
2012-12-01
Bias-correction methods applied to monthly temperature and precipitation data simulated by multiple General Circulation Models (GCMs) are evaluated in this study. Although various methods have been proposed recently, an intercomparison among them using multiple GCM simulations has seldom been reported. Moreover, no previous methods have addressed the issue how to adequately deal with the changes of the statistics of bias-corrected variables from the historical to future simulations. In this study, a new method which conserves the changes of mean and standard deviation of the uncorrected model simulation data is proposed, and then five previous bias-correction methods as well as the proposed new method are intercompared by applying them to monthly temperature and precipitation data simulated from 12 GCMs in the Coupled Model Intercomparison Project (CMIP3) archives. Parameters of each method are calibrated by using 1948-1972 observed data and validated in the 1974-1998 period. These methods are then applied to the GCM future simulations (2073-2097) and the bias-corrected data are intercompared. For the historical simulations, negligible difference can be found between observed and bias-corrected data. However, the differences in future simulations are large dependent on the characteristics of each method. The new method successfully conserves the changes in the mean, standard deviation and the coefficient of variation before and after bias-correction. The differences of bias-corrected data among methods are discussed according to their respective characteristics. Importantly, this study classifies available correction methods into two distinct categories, and articulates important features for each of them.
Kim, Kue Bum; Kwon, Hyun-Han; Han, Dawei
2015-11-01
In this paper, we present a comparative study of bias correction methods for regional climate model simulations considering the distributional parametric uncertainty underlying the observations/models. In traditional bias correction schemes, the statistics of the simulated model outputs are adjusted to those of the observation data. However, the model output and the observation data are only one case (i.e., realization) out of many possibilities, rather than being sampled from the entire population of a certain distribution due to internal climate variability. This issue has not been considered in the bias correction schemes of the existing climate change studies. Here, three approaches are employed to explore this issue, with the intention of providing a practical tool for bias correction of daily rainfall for use in hydrologic models ((1) conventional method, (2) non-informative Bayesian method, and (3) informative Bayesian method using a Weather Generator (WG) data). The results show some plausible uncertainty ranges of precipitation after correcting for the bias of RCM precipitation. The informative Bayesian approach shows a narrower uncertainty range by approximately 25-45% than the non-informative Bayesian method after bias correction for the baseline period. This indicates that the prior distribution derived from WG may assist in reducing the uncertainty associated with parameters. The implications of our results are of great importance in hydrological impact assessments of climate change because they are related to actions for mitigation and adaptation to climate change. Since this is a proof of concept study that mainly illustrates the logic of the analysis for uncertainty-based bias correction, future research exploring the impacts of uncertainty on climate impact assessments and how to utilize uncertainty while planning mitigation and adaptation strategies is still needed.
Statistics of football dynamics
Mendes, R. S.; Malacarne, L. C.; Anteneodo, C.
2007-06-01
We investigate the dynamics of football matches. Our goal is to characterize statistically the temporal sequence of ball movements in this collective sport game, searching for traits of complex behavior. Data were collected over a variety of matches in South American, European and World championships throughout 2005 and 2006. We show that the statistics of ball touches presents power-law tails and can be described by q-gamma distributions. To explain such behavior we propose a model that provides information on the characteristics of football dynamics. Furthermore, we discuss the statistics of duration of out-of-play intervals, not directly related to the previous scenario.
Statistics of football dynamics
Mendes, R S; Anteneodo, C
2007-01-01
We investigate the dynamics of football matches. Our goal is to characterize statistically the temporal sequence of ball movements in this collective sport game, searching for traits of complex behavior. Data were collected over a variety of matches in South American, European and World championships throughout 2005 and 2006. We show that the statistics of ball touches presents power-law tails and can be described by $q$-gamma distributions. To explain such behavior we propose a model that provides information on the characteristics of football dynamics. Furthermore, we discuss the statistics of duration of out-of-play intervals, not directly related to the previous scenario.
D'Alessio, Michael
2012-01-01
AP Statistics Crash Course - Gets You a Higher Advanced Placement Score in Less Time Crash Course is perfect for the time-crunched student, the last-minute studier, or anyone who wants a refresher on the subject. AP Statistics Crash Course gives you: Targeted, Focused Review - Study Only What You Need to Know Crash Course is based on an in-depth analysis of the AP Statistics course description outline and actual Advanced Placement test questions. It covers only the information tested on the exam, so you can make the most of your valuable study time. Our easy-to-read format covers: exploring da
Statistics a complete introduction
Graham, Alan
2013-01-01
Statistics: A Complete Introduction is the most comprehensive yet easy-to-use introduction to using Statistics. Written by a leading expert, this book will help you if you are studying for an important exam or essay, or if you simply want to improve your knowledge. The book covers all the key areas of Statistics including graphs, data interpretation, spreadsheets, regression, correlation and probability. Everything you will need is here in this one book. Each chapter includes not only an explanation of the knowledge and skills you need, but also worked examples and test questions.
Mayer, Michael
2009-01-01
In 1948, W. Hoeffding introduced a large class of unbiased estimators called U-statistics, defined as the average value of a real-valued m-variate function h calculated at all possible sets of m points from a random sample. In the present paper, we investigate the corresponding robust analogue which we call U-quantile-statistics. We are concerned with the asymptotic behavior of the sample p-quantile of such function h instead of its average. Alternatively, U-quantile-statistics can be viewed ...
Huizingh, Eelko K R E
2007-01-01
Accessibly written and easy to use, Applied Statistics Using SPSS is an all-in-one self-study guide to SPSS and do-it-yourself guide to statistics. Based around the needs of undergraduate students embarking on their own research project, the text's self-help style is designed to boost the skills and confidence of those that will need to use SPSS in the course of doing their research project. The book is pedagogically well developed and contains many screen dumps and exercises, glossary terms and worked examples. Divided into two parts, Applied Statistics Using SPSS covers :
Statistical Pattern Recognition
Webb, Andrew R
2011-01-01
Statistical pattern recognition relates to the use of statistical techniques for analysing data measurements in order to extract information and make justified decisions. It is a very active area of study and research, which has seen many advances in recent years. Applications such as data mining, web searching, multimedia data retrieval, face recognition, and cursive handwriting recognition, all require robust and efficient pattern recognition techniques. This third edition provides an introduction to statistical pattern theory and techniques, with material drawn from a wide range of fields,
Evolutionary Statistical Procedures
Baragona, Roberto; Poli, Irene
2011-01-01
This proposed text appears to be a good introduction to evolutionary computation for use in applied statistics research. The authors draw from a vast base of knowledge about the current literature in both the design of evolutionary algorithms and statistical techniques. Modern statistical research is on the threshold of solving increasingly complex problems in high dimensions, and the generalization of its methodology to parameters whose estimators do not follow mathematically simple distributions is underway. Many of these challenges involve optimizing functions for which analytic solutions a
Liao, Tim Futing
2011-01-01
An incomparably useful examination of statistical methods for comparisonThe nature of doing science, be it natural or social, inevitably calls for comparison. Statistical methods are at the heart of such comparison, for they not only help us gain understanding of the world around us but often define how our research is to be carried out. The need to compare between groups is best exemplified by experiments, which have clearly defined statistical methods. However, true experiments are not always possible. What complicates the matter more is a great deal of diversity in factors that are not inde
Wallis, W Allen
2014-01-01
Focusing on everyday applications as well as those of scientific research, this classic of modern statistical methods requires little to no mathematical background. Readers develop basic skills for evaluating and using statistical data. Lively, relevant examples include applications to business, government, social and physical sciences, genetics, medicine, and public health. ""W. Allen Wallis and Harry V. Roberts have made statistics fascinating."" - The New York Times ""The authors have set out with considerable success, to write a text which would be of interest and value to the student who,
Statistics of genome architecture
International Nuclear Information System (INIS)
The main statistical distributions applicable to the analysis of genome architecture and genome tracks are briefly discussed and critically assessed. Although the observed features in distributions of element lengths can be equally well fitted by the different statistical approximations, the interpretation of observed regularities may strongly depend on the chosen scheme. We discuss the possible evolution scenarios and describe the main characteristics obtained with different distributions. The expression for the assessment of levels in hierarchical chromatin folding is derived and the quantitative measure of genome architecture inhomogeneity is suggested. This theory provides the ground for the regular statistical study of genome architecture and genome tracks.
Mauro, John
2013-01-01
Written to reveal statistical deceptions often thrust upon unsuspecting journalists, this book views the use of numbers from a public perspective. Illustrating how the statistical naivete of journalists often nourishes quantitative misinformation, the author's intent is to make journalists more critical appraisers of numerical data so that in reporting them they do not deceive the public. The book frequently uses actual reported examples of misused statistical data reported by mass media and describes how journalists can avoid being taken in by them. Because reports of survey findings seldom g
Fluency and belief bias in deductive reasoning: new indices for old effects.
Trippas, Dries; Handley, Simon J; Verde, Michael F
2014-01-01
Models based on signal detection theory (SDT) have occupied a prominent role in domains such as perception, categorization, and memory. Recent work by Dube et al. (2010) suggests that the framework may also offer important insights in the domain of deductive reasoning. Belief bias in reasoning has traditionally been examined using indices based on raw endorsement rates-indices that critics have claimed are highly problematic. We discuss a new set of SDT indices fit for the investigation belief bias and apply them to new data examining the effect of perceptual disfluency on belief bias in syllogisms. In contrast to the traditional approach, the SDT indices do not violate important statistical assumptions, resulting in a decreased Type 1 error rate. Based on analyses using these novel indices we demonstrate that perceptual disfluency leads to decreased reasoning accuracy, contrary to predictions. Disfluency also appears to eliminate the typical link found between cognitive ability and the effect of beliefs on accuracy. Finally, replicating previous work, we demonstrate that cognitive ability leads to an increase in reasoning accuracy and a decrease in the response bias component of belief bias. PMID:25009515
Less than meets the eye: reappraising the clinical relevance of attentional bias in addiction.
Christiansen, Paul; Schoenmakers, Tim M; Field, Matt
2015-05-01
Recent years have seen an explosion of interest in attentional bias in addiction, particularly its clinical relevance. Specifically, numerous articles claimed to demonstrate either that (1) attentional bias measured in treatment settings could predict subsequent relapse to substance use, or (2) direct modification of attentional bias reduced substance use and improved treatment outcomes. In this paper, we critically evaluate empirical studies that investigated these issues. We show that the evidence regarding both of these claims is decidedly mixed, and that many of the studies that appear to yield positive findings have serious methodological and statistical limitations. We contend that the available literature suggests that attentional bias for drug cues fluctuates within individuals because it is an output of the underlying motivational state at that moment in time, but there is no convincing evidence that it exerts a causal influence on substance use. Future research should make use of experience sampling methodology to characterise the clinical significance of fluctuations in attentional bias over time. PMID:25453782
Stochastic bias-correction of daily rainfall scenarios for hydrological applications
Directory of Open Access Journals (Sweden)
I. Portoghese
2011-09-01
Full Text Available The accuracy of rainfall predictions provided by climate models is crucial for the assessment of climate change impacts on hydrological processes. In fact, the presence of bias in downscaled precipitation may produce large bias in the assessment of soil moisture dynamics, river flows and groundwater recharge.
In this study, a comparison between statistical properties of rainfall observations and model control simulations from a Regional Climate Model (RCM was performed through a robust and meaningful representation of the precipitation process. The output of the adopted RCM was analysed and re-scaled exploiting the structure of a stochastic model of the point rainfall process. In particular, the stochastic model is able to adequately reproduce the rainfall intermittency at the synoptic scale, which is one of the crucial aspects for the Mediterranean environments. Possible alteration in the local rainfall regime was investigated by means of the historical daily time-series from a dense rain-gauge network, which were also used for the analysis of the RCM bias in terms of dry and wet periods and storm intensity. The result is a stochastic scheme for bias-correction at the RCM-cell scale, which produces a realistic representation of the daily rainfall intermittency and precipitation depths, though a residual bias in the storm intensity of longer storm events persists.
Investigating and correcting plasma DNA sequencing coverage bias to enhance aneuploidy discovery.
Directory of Open Access Journals (Sweden)
Dineika Chandrananda
Full Text Available Pregnant women carry a mixture of cell-free DNA fragments from self and fetus (non-self in their circulation. In recent years multiple independent studies have demonstrated the ability to detect fetal trisomies such as trisomy 21, the cause of Down syndrome, by Next-Generation Sequencing of maternal plasma. The current clinical tests based on this approach show very high sensitivity and specificity, although as yet they have not become the standard diagnostic test. Here we describe improvements to the analysis of the sequencing data by reducing GC bias and better handling of the genomic repeats. We show substantial improvements in the sensitivity of the standard trisomy 21 statistical tests, which we measure by artificially reducing read coverage. We also explore the bias stemming from the natural cleavage of plasma DNA by examining DNA motifs and position specific base distributions. We propose a model to correct this fragmentation bias and observe that incorporating this bias does not lead to any further improvements in the detection of fetal trisomy. The improved bias corrections that we demonstrate in this work can be readily adopted into existing fetal trisomy detection protocols and should also lead to improvements in sub-chromosomal copy number variation detection.
Fluency and belief bias in deductive reasoning: New indices for old effects
Directory of Open Access Journals (Sweden)
Dries eTrippas
2014-06-01
Full Text Available Models based on signal detection theory (SDT have occupied a prominent role in domains such as perception, categorisation, and memory. Recent work by Dube et al. (2010 suggests that the framework may also offer important insights in the domain of deductive reasoning. Belief bias in reasoning has traditionally been examined using indices based on raw endorsement rates – indices that critics have claimed are highly problematic. We discuss a new set of SDT indices fit for the investigation belief bias and apply them to new data examining the effect of perceptual disfluency on belief bias in syllogisms. In contrast to the traditional approach, the SDT indices do not violate important statistical assumptions, resulting in a decreased Type 1 error rate. Based on analyses using these novel indices we demonstrate that disfluency leads to decreased reasoning accuracy, contrary to predictions. Disfluency also appears to eliminate the typical link found between cognitive ability and the effect of beliefs on accuracy. Finally, replicating previous work, we demonstrate that cognitive ability leads to an increase in reasoning accuracy and a decrease in the response bias component of belief bias.
Audibility and visual biasing in speech perception
Clement, Bart Richard
Although speech perception has been considered a predominantly auditory phenomenon, large benefits from vision in degraded acoustic conditions suggest integration of audition and vision. More direct evidence of this comes from studies of audiovisual disparity that demonstrate vision can bias and even dominate perception (McGurk & MacDonald, 1976). It has been observed that hearing-impaired listeners demonstrate more visual biasing than normally hearing listeners (Walden et al., 1990). It is argued here that stimulus audibility must be equated across groups before true differences can be established. In the present investigation, effects of visual biasing on perception were examined as audibility was degraded for 12 young normally hearing listeners. Biasing was determined by quantifying the degree to which listener identification functions for a single synthetic auditory /ba-da-ga/ continuum changed across two conditions: (1)an auditory-only listening condition; and (2)an auditory-visual condition in which every item of the continuum was synchronized with visual articulations of the consonant-vowel (CV) tokens /ba/ and /ga/, as spoken by each of two talkers. Audibility was altered by presenting the conditions in quiet and in noise at each of three signal-to- noise (S/N) ratios. For the visual-/ba/ context, large effects of audibility were found. As audibility decreased, visual biasing increased. A large talker effect also was found, with one talker eliciting more biasing than the other. An independent lipreading measure demonstrated that this talker was more visually intelligible than the other. For the visual-/ga/ context, audibility and talker effects were less robust, possibly obscured by strong listener effects, which were characterized by marked differences in perceptual processing patterns among participants. Some demonstrated substantial biasing whereas others demonstrated little, indicating a strong reliance on audition even in severely degraded acoustic
Better confidence intervals for left censored data using bias corrected bootstrap method
International Nuclear Information System (INIS)
Estimation of the 95% confidence intervals of the population parameters of small sized (say <= 30) environmental data samples under conventional statistical methodologies are error prone because the probability density function associated with the specified data sets, most of the times, is questionable. Therefore, in instances when the distribution of a statistic is unknown, nonparametric methods such as bootstrap override the conventional ones. The nonparametric (percentile) bootstrap method has been used to evaluate the confidence intervals of the mean. This paper describes the application of bias-corrected percentile bootstrap method that yields better confidence intervals than the percentile bootstrap method. An inter-comparative study of the two methods is also carried out. A case study with air activity data recorded from a specific Indian nuclear power plant is presented to support the superiority of bias corrected bootstrap method over the percentile bootstrap method and the conventional students -t method. (author)
Security of biased BB84 quantum key distribution with finite resource
International Nuclear Information System (INIS)
In the original BB84 quantum key distribution protocol, the states are prepared and measured randomly, which lose the unmatched detection results. To improve the sifting efficiency, biased bases selection BB84 protocol is proposed. Meanwhile, a practical quantum key distribution protocol can only transmit a finite number of signals, resulting in keys of finite length. The previous techniques for finite-key analysis focus mainly on the statistical fluctuations of the error rates and yields of the qubits. However, the prior choice probabilities of the two bases also have fluctuations by taking into account the finite-size effect. In this paper, we discuss the security of biased decoy state BB84 protocol with finite resources by considering all of the statistical fluctuations. The results can be directly used in the experimental realizations. (general)
Weak lensing statistics from the Coyote Universe
Eifler, Tim
2010-01-01
Analyzing future weak lensing data sets from KIDS, DES, LSST, Euclid, WFIRST requires precise predictions for the weak lensing measures. In this paper we present a weak lensing prediction code based on the Coyote Universe emulator. The Coyote Universe emulator predicts the (non-linear) power spectrum of density fluctuations (P_delta) to high accuracy for k \\in [0.002;3.4] h/Mpc within the redshift interval z \\in [0;1], outside this regime we extend P_delta using a modified Halofit code. This pipeline is used to calculate various second-order cosmic shear statistics, e.g., shear power spectrum, shear-shear correlation function, ring statistics and COSEBIs (Complete Orthogonal Set of EB-mode Integrals), and we examine how the upper limit in k (and z) to which P_delta is known, impacts on these statistics. For example, we find that k_max~8 h/Mpc causes a bias in the shear power spectrum at l~4000 that is comparable to the statistical errors (intrinsic shape-noise and cosmic variance) of a DES-like survey, wherea...
Directory of Open Access Journals (Sweden)
Lash Timothy L
2007-11-01
Full Text Available Abstract Background The associations of pesticide exposure with disease outcomes are estimated without the benefit of a randomized design. For this reason and others, these studies are susceptible to systematic errors. I analyzed studies of the associations between alachlor and glyphosate exposure and cancer incidence, both derived from the Agricultural Health Study cohort, to quantify the bias and uncertainty potentially attributable to systematic error. Methods For each study, I identified the prominent result and important sources of systematic error that might affect it. I assigned probability distributions to the bias parameters that allow quantification of the bias, drew a value at random from each assigned distribution, and calculated the estimate of effect adjusted for the biases. By repeating the draw and adjustment process over multiple iterations, I generated a frequency distribution of adjusted results, from which I obtained a point estimate and simulation interval. These methods were applied without access to the primary record-level dataset. Results The conventional estimates of effect associating alachlor and glyphosate exposure with cancer incidence were likely biased away from the null and understated the uncertainty by quantifying only random error. For example, the conventional p-value for a test of trend in the alachlor study equaled 0.02, whereas fewer than 20% of the bias analysis iterations yielded a p-value of 0.02 or lower. Similarly, the conventional fully-adjusted result associating glyphosate exposure with multiple myleoma equaled 2.6 with 95% confidence interval of 0.7 to 9.4. The frequency distribution generated by the bias analysis yielded a median hazard ratio equal to 1.5 with 95% simulation interval of 0.4 to 8.9, which was 66% wider than the conventional interval. Conclusion Bias analysis provides a more complete picture of true uncertainty than conventional frequentist statistical analysis accompanied by a
Single-Receiver GPS Phase Bias Resolution
Bertiger, William I.; Haines, Bruce J.; Weiss, Jan P.; Harvey, Nathaniel E.
2010-01-01
Existing software has been modified to yield the benefits of integer fixed double-differenced GPS-phased ambiguities when processing data from a single GPS receiver with no access to any other GPS receiver data. When the double-differenced combination of phase biases can be fixed reliably, a significant improvement in solution accuracy is obtained. This innovation uses a large global set of GPS receivers (40 to 80 receivers) to solve for the GPS satellite orbits and clocks (along with any other parameters). In this process, integer ambiguities are fixed and information on the ambiguity constraints is saved. For each GPS transmitter/receiver pair, the process saves the arc start and stop times, the wide-lane average value for the arc, the standard deviation of the wide lane, and the dual-frequency phase bias after bias fixing for the arc. The second step of the process uses the orbit and clock information, the bias information from the global solution, and only data from the single receiver to resolve double-differenced phase combinations. It is called "resolved" instead of "fixed" because constraints are introduced into the problem with a finite data weight to better account for possible errors. A receiver in orbit has much shorter continuous passes of data than a receiver fixed to the Earth. The method has parameters to account for this. In particular, differences in drifting wide-lane values must be handled differently. The first step of the process is automated, using two JPL software sets, Longarc and Gipsy-Oasis. The resulting orbit/clock and bias information files are posted on anonymous ftp for use by any licensed Gipsy-Oasis user. The second step is implemented in the Gipsy-Oasis executable, gd2p.pl, which automates the entire process, including fetching the information from anonymous ftp
Grégoire, G.
2016-05-01
This chapter is devoted to two objectives. The first one is to answer the request expressed by attendees of the first Astrostatistics School (Annecy, October 2013) to be provided with an elementary vademecum of statistics that would facilitate understanding of the given courses. In this spirit we recall very basic notions, that is definitions and properties that we think sufficient to benefit from courses given in the Astrostatistical School. Thus we give briefly definitions and elementary properties on random variables and vectors, distributions, estimation and tests, maximum likelihood methodology. We intend to present basic ideas in a hopefully comprehensible way. We do not try to give a rigorous presentation, and due to the place devoted to this chapter, can cover only a rather limited field of statistics. The second aim is to focus on some statistical tools that are useful in classification: basic introduction to Bayesian statistics, maximum likelihood methodology, Gaussian vectors and Gaussian mixture models.
Statistics in Atmospheric Science
Solow, Andrew R.
2003-01-01
This paper reviews the use of statistical methods in atmospheric science. The applications covered include the development, assessment and use of numerical physical models of the atmosphere and more empirical analysis unconnected to physical models.
Medicaid Drug Claims Statistics
U.S. Department of Health & Human Services — The Medicaid Drug Claims Statistics CD is a useful tool that conveniently breaks up Medicaid claim counts and separates them by quarter and includes an annual count.