Categorical data analysis
Undergraduate · Math
Syllabus focus
Topics typically covered
Click a topic for the full text and related unit practice.
Undergraduate Categorical data analysis — outline derived from course README sections and typical US statistics syllabi (OpenIntro / standard OER where applicable).
Contingency tables
- Two-way tables: independence — Two-way tables: independence
- Association — Association
- Chi-square tests — Chi-square tests
- Expected counts — Expected counts
- Odds ratios — Odds ratios
- Relative risk for 2×2 tables — Relative risk for 2×2 tables
- Exact tests for small samples — Exact tests for small samples
- Stratified tables — Stratified tables
- Mantel–Haenszel methods — Mantel–Haenszel methods
Logistic and log-linear models
- Logistic regression for binary outcomes — Logistic regression for binary outcomes
- Multinomial — Multinomial
- Ordinal logistic models (intro) — Ordinal logistic models (intro)
- Log-linear models for count data — Log-linear models for count data
- Model selection and deviance — Model selection and deviance
- Overdispersion — Overdispersion
- Quasi-likelihood (intro) — Quasi-likelihood (intro)
Advanced categorical methods
- Repeated categorical data: GEE preview — Repeated categorical data: GEE preview
- Matched-pair designs — Matched-pair designs
- McNemar's test — McNemar's test
- Agresti-style interpretation of odds ratios — Agresti-style interpretation of odds ratios
- Residual analysis for GLMs — Residual analysis for GLMs
Study units
Each unit includes a study guide, worksheets, review, practice test, and answer key. One unit is free; subscribe for the full class.
- Contingency tables
Two-way tables: independence
Coming soon - Logistic and log-linear models
Logistic regression for binary outcomes
Coming soon - Advanced categorical methods
Repeated categorical data: GEE preview
Coming soon
Notes
Undergraduate Categorical data analysis — outline derived from course README sections and typical US statistics syllabi (OpenIntro / standard OER where applicable). Topic outline: `content/topics/undergraduate/categorical.json`.