STAT 480
Statistical Consulting and Data Analysis
Fall 2026
Topics
- R refresher
- Data wrangling and cleaning
- Descriptive statistics
- Missing data
- Visualization
- Linear regression
- Model comparison and sensitivity analysis
- Logistic and categorical regression
- Communicating statistical findings
Readings
- Hadley Wickham, Mine Çetinkaya-Rundel and Garrett Grolemund. R for Data Science.
- Slides and additional files supplied on Moodle.
Sources
- Course catalogue ↗2026–2027
- Syllabus or course outline ↗Fall 2026
- Historical course outline ↗Winter 2024
- Historical course outline ↗Winter 2024
- Historical course outline ↗Winter 2023
- Historical course outline ↗Winter 2022
- Fall 2026 outline. Course header explicitly lists STAT 480, MAST 678, MAST 881. Explicitly no required textbook; R for Data Science is described as a useful resource.
- Historical source. Generic Textbook/References headings remain requirement-unspecified. Bibliographic editions and years are retained as printed; source inconsistencies may remain. Automated extraction with conservative filtering; distinct bibliography strings screened for false positives; entire syllabus not manually reviewed.
- Historical source. Generic Textbook/References headings remain requirement-unspecified. Bibliographic editions and years are retained as printed; source inconsistencies may remain. Automated extraction with conservative filtering; distinct bibliography strings screened for false positives; entire syllabus not manually reviewed.
- Historical source. Generic Textbook/References headings remain requirement-unspecified. Bibliographic editions and years are retained as printed; source inconsistencies may remain. Automated extraction with conservative filtering; distinct bibliography strings screened for false positives; entire syllabus not manually reviewed.
- Historical source. Generic Textbook/References headings remain requirement-unspecified. Bibliographic editions and years are retained as printed; source inconsistencies may remain. Automated extraction with conservative filtering; distinct bibliography strings screened for false positives; entire syllabus not manually reviewed.