STAT 333-Nonparametric Statistics Methods 2026 (1448H)

Nonparametric Statistics Methods (STAT 333)

Course general Description:

A course on distribution-free and nonparametric statistical methods focuses primarily on testing techniques that do not rely on the assumption of a normal distribution.

The curriculum covers a comprehensive range of nonparametric statistics topics and methods, including:

• One-Sample Tests: The Kolmogorov-Smirnov one-sample test, the sign test, and the Wilcoxon signed-rank test.
• Two-Sample Tests: The Mann-Whitney U test and the Kolmogorov-Smirnov two-sample test.
• Multi-Sample & Repeated Measures Tests: The Kruskal-Wallis H test and the Friedman test.
• Correlation Measures: Spearman's rank-order, point-biserial, and biserial correlations.
• Categorical Data Analysis: The chi-square ($\chi^2$) goodness-of-fit test (for unequal category frequencies), the chi-square ($\chi^2$) test for independence, and Fisher's exact test.
• Tests for Randomness: Evaluating data independence and randomness.

Students will utilize statistical software (R) to carry out all nonparametric procedures.