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| Campus | Haverford |
| Semester | Fall 2025 |
| Registration ID | STATH396A001 |
| Course Title | Advanced Topics in Probability and Statistics |
| Credit | 1.00 |
| Department | Statistics |
| Instructor | Butler,Lynne |
| Times and Days | TTh 11:30am-12:55pm
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| Room Location | |
| Additional Course Info | Class Number: 2737 A 300-level course in probability and/or statistics, with the particular topic(s) varying each time it is offered. Fall 2025: Categorical Data Analysis is an applied statistics course, intended for students who are mathematically sophisticated but statistically inexperienced. It has a prerequisite of Math 218, which covers discrete distributions that are used to model categorical data (the binomial and multinomial, geometric and hypergeometric, and Poisson distributions). The course will present methods for analyzing categorical data, including standard methods for contingency tables such as odds ratios, tests of independence and various measures of association, generalized linear models for binary and count data, logistic regression for binomial data, loglinear models for Poisson data, models for paired samples with categorical responses, and generalized linear mixed models. Prerequisite(s): MATH 218.; Enrollment Limit: 15 Div: II; Natural Science, Quantitative (; Hav: NA, QU) |
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