Failure to Replicate Burton, Harris, Shah & Hahn (2021): There is No Belief Update Bias for Neutral Events

We investigate Burton’s et al.’s, recent findings of a belief update bias for neutral events. First, we find that Burton et al. fail to replicate their own findings in three out of the four experiments they conduct. When aggregating their data over their four experiments (500 participants) the results do not support a belief update bias for neutral events. In an attempt to replicate their findings, we collect a new data set employing the original belief update task design, but with neutral events. A belief update bias for neutral events is not observed. Finally, we highlight the wide range of statistical errors and confounds in Burton et al.’s design and analysis and the misleading statements they make.

Statistical analysis of cytogenetic data

Using the data obtained in a cytogenetic study as an example, we consider the typical errors that are made when performing statistical analysis. Widespread but flawed statistical analysis inevitably produces biased results and increases the likelihood of incorrect scientific conclusions. Errors occur due to not taking into account the study design and the structure of the analyzed data. The article shows how the numerical imbalance of the data set leads to a bias in the result. Using a dataset as an example, it explains how to balance the complex. It shows the advantage of presenting sample indicators with confidence intervals instead of statistical errors. Attention is drawn to the need to take into account the size of the analyzed shares when choosing a statistical method. It shows how the same data set can be analyzed in different ways depending on the purpose of the study. The algorithm of correct statistical analysis and the form of the tabular presentation of the results are described. Keywords: data structure, numerically unbalanced complex, confidence interval.

Predicting Strength of Titanium Alloys Using Aluminum and Molybdenum Equivalents at Operating Temperatures

This study contains the results of statistical studies of strength of sheeted products and bars made from α-, near α-, and α+β titanium alloys based on their composition. Based on summarizing the literature data, we have studied the ultimate tensile strength after mill annealing of 30 serial and experimental alloys at testing temperatures between 20 and 600°C. We have also substantiated the possibility to evaluate the tensile strength of semi-finished products using the strength equivalents (such as aluminum and molybdenum) of alloying elements and impurities at various temperatures. We have put forth models that help to predict the ultimate strength of titanium alloys based on their composition and the operating temperature with a confidence level of 0.95 and statistical errors comparable with the regulated spread.

Dispersion-theoretical analysis of the electromagnetic form factors of the nucleon: Past, present and future

We review the dispersion-theoretical analysis of the electromagnetic form factors of the nucleon. We emphasize in particular the role of unitarity and analyticity in the construction of the isoscalar and isovector spectral functions. We present new results on the extraction of the nucleon radii, the electric and magnetic form factors and the extraction of $$\omega $$ ω -meson couplings. All this is supplemented by a detailed calculation of the theoretical uncertainties, using bootstrap and Bayesian methods to pin down the statistical errors, while systematic errors are determined from variations of the spectral functions. We also discuss the physics of the time-like form factors and point out further issues to be addressed in this framework.

The pp → W(→ lν) + γ process at next-to-next-to-leading order

We present details of the calculation of the pp → W(→ lν)γ process at next-to-next-to-leading order in QCD, calculated using the jettiness slicing method. The calculation is based entirely on analytic amplitudes. Because of the radiation zero, the NLO QCD contribution from the gq channel is as important as the contribution from the Born $$ q\overline{q} $$ q q ¯ process, disrupting the normal counting of leading and sub-leading contributions. We also assess the importance of electroweak (EW) corrections, including the EW corrections to both the six-parton channel 0 →$$ \overline{u} d\nu {e}^{+}\gamma g $$ u ¯ dν e + γg and the five-parton channel 0 →$$ \overline{u} d\nu {e}^{+}\gamma $$ u ¯ dν e + γ . Previous experimental results have been shown to agree with theoretical predictions, taking into account the large experimental errors. With the advent of run II data from the LHC, the statistical errors on the data will decrease, and will be competitive with the error on theoretical predictions for the first time. We present numerical results for $$ \sqrt{s} $$ s = 7 and 13 TeV. Analytic results for the one-loop six-parton QCD amplitude and the tree-level seven-parton QCD amplitude are presented in appendices.

A python program to model and analyze wind speed data

A python program has been developed to analyze wind distributions using the Weibull density function. A two-parameter Weibull function is frequently used to model and assess wind potential and wind distribution. This python program finds first Weibull parameters from the recorded wind data by five different methods, namely, Empirical Method(EPM), Method of Moment (MoM), Energy Pattern Factor Method (EPFM), Maximum Likelihood Method (MLM), Modified Maximum Likelihood Method (MMLM), the parameters are then used to find theoretically fitted pdfs. The program is implemented on wind distribution of two cities of Pakistan (Chakri and Sadiq Abad). The program-generated pdfs were plotted with the histogram of recorded data, the fitting was excellent. To check the validity of the fitted pdfs, statistical errors Root Mean Square (RMSE), MeanAbsolute Percent Error (MAPE), Mean Absolute Error (MABE), and Chi-square statistic are calculated. In all cases,these statistical errors are well below the acceptance range. Both pictorial results and numerical values of statistical errors indicate the performance of the python program to analyze wind speed data

Statistical Errors in X-Ray Triaxial Stress Analysis by Cos α Method

Currently, the sin2ψ method is established as an effective technique as how to measure the residual stress state of metal materials non-destructively by X-ray diffraction. In recent years, new X-ray stress measurements with two-dimensional detector are developed and spreading in the world. There is the cosα method as one of the new techniques. However, the research about the statistical errors in the method continues. The measurement theory of the cos α method is reviewed on the triaxial stress state. The triaxial stress analysis by the method is examined and discussed from a viewpoint of the derived errors for the determination.