Multi-Sample Functional Statistical Data Analysis
TEXAS A AND M UNIV COLLEGE STATION DEPT OF STATISTICS
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This paper discusses a functional approach to the problem of comparison of multi-samples two samples or c samples, where c or 2. The data consists of c random samples whose probability distributions are to be tested for equality. A diversity of statistics to test equality of c samples are presented in a unified framework with the aim of helping the researcher choose the optimal procedures which provide greatest insight about how the samples differ in their distributions. Concepts discussed are sample distribution functions ranks mid-distribution function two- sample t test and nonparametric Wilcoxon test multi-sample analysis of variance and Kruskal Wallis test Anderson Darling and Cramer von Mises tests components and linear rank statistics comparison distribution and comparison density functions, especially for discrete distributions components with orthogonal polynomial score functions chi-square tests and their components.
- Statistics and Probability