Generally, multiple statistical analysis methods can be applied for certain kind of data, and conclusion could differ, depending on the selected statistical method. Therefore, it is necessary to fully understand the performance of each statistical method and to examine which method is appropriate to use and to standardize statistical methods for toxicity studies to be carried out routinely. Sev...

Numerous functional magnetic resonance imaging (fMRI) data analysis strategies have been used by different laboratories to enhance the detection of brain activation. A consensus has not been achieved regarding the relative statistical power of different strategies. In this report, we compared several commonly-used data analysis strategies for conventional (nonechoplanar imaging) fMRI data by ev...

This paper provides a test method to make a fair comparison between different heuristics in structure optimization. When statistical methods are applied to the structural optimization (namely heuristics or meta-heuristics with several tunable parameters and starting seeds), the "one problem - one result" is extremely far from the fair comparison. From statistical point of view, the minimal requ...

This paper presents two Bayesian alternatives to the chi-squared test for determining whether a pair of categorical data sets were generated from the same underlying distribution. It then discusses such alternatives for the Kolmogorov-Smirnov test, which is often used when the data sets consist of real numbers.

Abstract Patient-based quality control (PBQC) involves monitoring for shifts in patient results to detect analytical problems. Established methods perform well, but only assays with high volumes and approximately normal result distributions. Recent publications have described the average of deltas (AOD) as a way generalize PBQC more broadly. Here we propose nonparametric analysis (NPAOD). To il...

The importance of normal distribution is undeniable since it is an underlying assumption of many statistical procedures such as t-tests, linear regression analysis, discriminant analysis and Analysis of Variance (ANOVA). When the normality assumption is violated, interpretation and inferences may not be reliable or valid. The three common procedures in assessing whether a random sample of indep...

Besides the opportunity for discovering new neutrino physics, solar neutrino measurements provide a sensitive probe of the solar interior, and thus a rigorous test of solar model predictions. We present model independent determinations of the neutrino spectrum by using relevant flux components as free parameters subject only to the luminosity constraint. (1) Without the Mikheyev-Smirnov-Wolfens...