Statistical Software-Data Processing-Concise Statistical Analysis (CS)

This software has three major functions: statistical analysis, research design, and statistical simulation.

In order to meet the needs of the majority of non-statistics professional researchers, the software has compiled multiple statistical analysis modules that can complete various statistical analyzes of common data, including:

Statistical description (mean, standard deviation, median, percentile, probability of binomial distribution and Poisson distribution);

Parameter estimation (confidence interval estimate of the population mean, confidence interval estimate of the population variance, confidence interval estimate of the population standard deviation, confidence interval estimate of the population rate of the binomial distribution, confidence interval estimate of the population mean of the Poisson distribution );

Hypothesis testing (grouped and paired t-test, u-test, analysis of variance and pairwise comparison of multiple sample means in group design, analysis of variance and pairwise comparison in matched group design, two or more group rank sum test and Pairwise comparison, paired rank sum test, matching group rank sum test and pairwise comparison, factorial design data square analysis, crossover design data analysis of variance, case follow-up data analysis, Ridit analysis, four-grid table data chi-square test, R× C table chi-square test, contingency table chi-square test and contingency coefficient calculation, hierarchical data hypothesis testing, hierarchical correlation analysis of two-way ordered data, circular distribution data analysis);

Linear correlation regression (calculation and hypothesis testing of product difference correlation coefficient, calculation and hypothesis testing of rank correlation coefficient, comparison of sample correlation coefficient and overall correlation coefficient, comparison and merger of two sample correlation coefficients, calculation and hypothesis of linear regression equation testing, using regression equations for statistical prediction and statistical control).

This software can estimate sample size and test power for a variety of study types.

Statistical simulation is a major feature of this software. Simulation can help users deeply understand the basic principles of statistics and can be used to assist teaching and self-study of statistics.