What This Document Is
This is a detailed syllabus for BSTT 511: Categorical Data Analysis, a graduate-level course offered at the University of Illinois at Chicago. It outlines the structure, content, and expectations for students enrolled in the course. This syllabus serves as a comprehensive guide to the topics explored within the realm of analyzing data that falls into distinct categories, rather than continuous measurements. It’s a foundational resource for understanding the course’s progression and assessment methods.
Why This Document Matters
This syllabus is essential for anyone considering enrolling in BSTT 511, as well as currently enrolled students. Prospective students can use it to determine if the course aligns with their academic and professional goals. Current students will benefit from having a clear roadmap of the semester, including scheduled topics, and important dates. Researchers and data analysts interested in understanding the course’s scope of categorical data analysis techniques will also find it valuable.
Topics Covered
* Foundations of estimation and inference for proportions.
* Goodness-of-fit testing for categorical data.
* Analysis of contingency tables (two-way and three-way).
* Measures of association for categorical variables.
* Log-linear modeling techniques and strategies.
* Logistic regression for binary outcomes and advanced designs.
* Models for ordinal and nominal responses.
* Generalized linear models and their applications.
* Regression models for count data (Poisson regression).
* Analysis of repeated measures data.
What This Document Provides
* A week-by-week schedule of topics to be covered.
* Information on statistical software (SAS) procedures utilized in the course.
* Key dates for assessments, including a midterm and final exam.
* An overview of the types of categorical data analysis methods explored.
* A structured learning path for mastering techniques in categorical data analysis.
* A clear understanding of the course’s expectations and requirements.