Appl Categorical Data Analysis
11:40am–12:55pm
HAMILTON HALL HAM 517
Morningside
Seat data provenance: Directory as of August 23, 2026 at 4:00 AM
Description
Prerequisites: STAT UN2103 is strongly recommended. Students without programming experience in R might find STAT UN2102 very helpful. This course covers statistical models amd methods for analyzing and drawing inferences for problems involving categofical data. The goals are familiarity and understanding of a substantial and integrated body of statistical methods that are used for such problems, experience in anlyzing data using these methods, and profficiency in communicating the results of such methods, and the ability to critically evaluate the use of such methods. Topics include binomial proportions, two-way and three-way contingency tables, logistic regression, log-linear models for large multi-way contingency tables, graphical methods. The statistical package R will be used
Reviews
Course experience
Aggregated across everyone who has taught this course.
No reviews matched yet.
Instructor quality
Aggregated across every course Casey Bradshaw has taught.
No reviews matched yet.
In your week
Where it meets
Flat map — motion reduced
Workload and grading
- Grading
- Not published
- Format
- Not published
- Credits
- 3 credits
Reported workload
From CULPA and Reddit reviews matched to this course.
No reviews matched yet.