Odd Semester

Non-Parametric Methods is a statistical course that focuses on data analysis techniques that don't require a specific distribution or parameterization. This course covers methods for hypothesis testing, confidence intervals, and regression analysis that are robust and flexible, making them suitable for small or irregularly distributed datasets. Students learn to apply non-parametric tests, such as the Wilcoxon rank-sum test and the Kruskal-Wallis test, and explore techniques like bootstrapping and permutation tests. By the end of the course, students can analyze and interpret complex data without relying on traditional parametric assumptions.