Standard syllabus
Nonparametric statistics · Undergraduate · Math
Learning objectives from the Nonparametric statistics syllabus, grouped by unit. Click an objective for study materials.
Topics typically covered
Click a topic for the full text and related unit practice.
Undergraduate Nonparametric statistics — outline derived from course README sections and typical US statistics syllabi (OpenIntro / standard OER where applicable).
One- and two-sample methods
- Sign test — Sign test
- Wilcoxon signed-rank test — Wilcoxon signed-rank test
- Wilcoxon rank-sum (Mann–Whitney) test — Wilcoxon rank-sum (Mann–Whitney) test
- Permutation tests: principles — Permutation tests: principles
- Examples — Examples
- Bootstrap hypothesis tests (introduction) — Bootstrap hypothesis tests (introduction)
- Rank correlation: Spearman — Rank correlation: Spearman
- Kendall — Kendall
K-sample and related methods
- Kruskal–Wallis test — Kruskal–Wallis test
- Friedman test for repeated measures — Friedman test for repeated measures
- Kolmogorov–Smirnov tests — Kolmogorov–Smirnov tests
- Nonparametric regression: kernel smoothing (intro) — Nonparametric regression: kernel smoothing (intro)
- Runs tests — Runs tests
- Goodness-of-fit (overview) — Goodness-of-fit (overview)
Density and smoothing
- Empirical distribution functions — Empirical distribution functions
- Kernel density estimation — Kernel density estimation
- Bandwidth selection (introduction) — Bandwidth selection (introduction)
- Comparison to parametric alternatives — Comparison to parametric alternatives
Learning objectives
Click an objective for study materials.
One- and two-sample methods
- Sign test — Sign test
- Wilcoxon signed-rank test — Wilcoxon signed-rank test
- Wilcoxon rank-sum (Mann–Whitney) test — Wilcoxon rank-sum (Mann–Whitney) test
- Permutation tests: principles — Permutation tests: principles
- Examples — Examples
- Bootstrap hypothesis tests (introduction) — Bootstrap hypothesis tests (introduction)
- Rank correlation: Spearman — Rank correlation: Spearman
- Kendall — Kendall
K-sample and related methods
- Kruskal–Wallis test — Kruskal–Wallis test
- Friedman test for repeated measures — Friedman test for repeated measures
- Kolmogorov–Smirnov tests — Kolmogorov–Smirnov tests
- Nonparametric regression: kernel smoothing (intro) — Nonparametric regression: kernel smoothing (intro)
- Runs tests — Runs tests
- Goodness-of-fit (overview) — Goodness-of-fit (overview)
Density and smoothing
- Empirical distribution functions — Empirical distribution functions
- Kernel density estimation — Kernel density estimation
- Bandwidth selection (introduction) — Bandwidth selection (introduction)
- Comparison to parametric alternatives — Comparison to parametric alternatives
Multi-Unit Problems
Course-level sets that combine skills across study units (coming soon).
Browse Multi-Unit ProblemsWhat each unit includes
Open a unit below for full materials. Typical resources:
- Study guide
- Exam Strategy
- Common Mistakes
- Worksheets
- Word problems
- Mixed Practice
- Multi-Unit Problems
- Review
- Practice test
- Answer key
Study units
Each unit includes a study guide, worksheets, review, practice test, and answer key. One unit is free; subscribe for the full class.
- One- and two-sample methods
Sign test
Coming soon - K-sample and related methods
Kruskal–Wallis test
Coming soon - Density and smoothing
Empirical distribution functions
Coming soon
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$1,162 · Nonparametric statistics · 18 tutoring hrs
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