STAT 435
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Nonparametric Statistical Methods
Statistics
College of Computational, Mathematical, & Physical Sciences
Course Description
Permutation tests, rank-based methods, analysis of contingency tables, bootstrap methods, curve fitting.
When Taught
Fall
Min
3
Fixed
3
Fixed
3
Fixed
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's exact test, Mantel-Haenszel test, McNemar's test
Title
Examples of Trade-Off
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
Title
Generalized Additive Models
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
