# STAT 435

## Nonparametric Statistical Methods

Statistics College of Physical and Mathematical Sciences

### Course Description

Permutation tests, rank-based methods, analysis of contingency tables, bootstrap methods, curve fitting.

### When Taught

Fall

Grade Rule 8: A, B, C, D, E, I (Standard grade rule)

3

3

3

0

### Title

Bootstrap Confidence Intervals

### Learning Outcome

Formulate and compute bootstrap (resampling) confidence intervals

### Title

Contingency Tables

### Learning Outcome

Compute the following tests for contingency tables: Fisher&#39;s exact test, Mantel-Haenszel test, McNemar&#39;s test

### Learning Outcome

Explain and provide examples of the trade-off between parametric assumptions and efficiency of statistical inference

### Title

Parametric Assumptions and Statistical Inference

### Learning Outcome

Explain and provide examples of the trade-off between parametric assumptions and efficiency of statistical inference

### Title

Compute Rank-Based Methods

### Learning Outcome

Compute the following rank-based methods: Wilcoxon Rank-Sum test, Mann-Whitney test, Signed-Rank test, Kruskal-Wallis test, Spearman Rank Correlation

### Learning Outcome

Compute generalized additive models (GAM) with splines or smoothers for possible nonlinear effects in R

### Title

Permutation Tests

### Learning Outcome

Formulate and compute permutation tests for 2-sample, K-sample, and contingency tables

### Title

Rank-Based Methods

### Learning Outcome

Compute the following rank-based methods: Wilcoxon Rank-Sum test, Mann-Whitney test, Signed-Rank test, Kruskal-Wallis test, and Spearman Rank Correlation