Comparative Analysis: Parametric and Non-Parametric Methods

Catalog description

Comparative Analysis: Parametric and Non-Parametric Methods is an applied graduate-level course that prepares public health students to select, apply, and interpret appropriate statistical tests for research data. Topics include One-Way and Two-Way ANOVA, Repeated Measures ANOVA, and non-parametric methods such as Wilcoxon Signed-Rank, Mann-Whitney U, Kruskal-Wallis, Friedman, Chi-Square, and Fisher’s Exact tests. Emphasis is placed on evaluating statistical assumptions, understanding effect size and power, and making evidence-based methodological decisions. Through hands-on assignments in R or SAS, students gain practical data analysis skills, culminating in a final project analyzing and reporting public health data using appropriate statistical approaches and interpretation standards.