Spring 2024

Categorical Data Analysis for the Greater Good

Listed in: Mathematics and Statistics, as STAT-436


Shu-Min Liao (Section 01)


The application of statistical methods for categorical data is ubiquitous in the modern world, especially in social sciences, biomedical research, and economics and business. However, many traditional statistical tools (like linear regression models) are not designed to handle observations classified into categories and thus inappropriate for analyzing such data. In this course, students will learn important theories and statistical methods specifically designed for visualizing and modeling categorical and ordinal data, while undertaking meaningful analyses and interpretations of complex real-world data that focus on common good issues of their choices. This course is ideal for students who seek to not only develop new statistical capacities but also apply their analytic skills to work for the greater good.

Requisite: STAT 230 and STAT 360, or equivalent experience by consent of the instructor. Spring semester. Professor Liao

How to handle overenrollment: Priority for Statistics majors

Students who enroll in this course will likely encounter and be expected to engage in the following intellectual skills, modes of learning, and assessment: quantitative work, problem sets, reading research articles, group work, use of computational software, projects, oral presentations

STAT 436 - LEC

Section 01
Tu 11:30 AM - 12:50 PM
Th 11:30 AM - 12:50 PM