DSC 532 - Categorical Data Analysis

Course Description: Introduction to analysis of categorical data and applications with implementation in computer languages such as Python, R, SAS, and Matlab. Develop proficiency in one-way to n-way frequency and contingency (crosstabulation) tables. Advance skills in logistic models with binary, ordinal, or nominal dependent variables. Six lecture hours and two laboratory hours per week for each week of the half-semester session.

Credit Hours: 3

Corequisite Courses: None
Prerequisite Courses: None
Additional Restrictions/ Requirements: None
Course Repeatability: Course may not be repeated

ADDITIONAL COURSE INFORMATION

Equivalent Courses: None
Undergraduate Crosslisting: None
Additional Course Fees: None
Course Attribute: None

Click here for the Spring 2025 Class Schedule.