Statistics
 

Nonparametric Statistical Methods

Nonparametric Statistical Methods
Permutation tests, rank-based methods, analysis of contingency tables, bootstrap methods, curve fitting.
STAT
435
 Hours3.0 Credit, 3.0 Lecture, 0.0 Lab
 PrerequisitesSTAT 330; or STAT 511
 TaughtFall
 ProgramsContaining STAT 435
Course Outcomes: 

Examples of Trade-Off

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

Parametric Assumptions and Statistical Inference

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

Rank-Based Methods

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

Compute Rank-Based Methods

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

Permutation Tests

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

Contingency Tables

Compute the following tests for contingency tables: Fisher's exact test, Mantel-Haenszel test, McNemar's test

Bootstrap Confidence Intervals

Formulate and compute bootstrap (resampling) confidence intervals

Generalized Additive Models

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