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Sep 04, 2024
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STAT 661 - Categorical Data Analysis Units: 2 Applied methods for discrete data. Topics may include: proportions and counts, contingency tables, loglinear models, logistic regression, Poisson regression, generalized linear models. Data integrity. Computing techniques and analysis of discrete data. Use of SAS. Report writing.
Prerequisites: STAT 631 and STAT 632. Possible Instructional Methods: On-ground. Grading: A-F grading only. Cross-listed: BSTA 661. Student Learning Outcomes - Upon successful completion of this course students will be able to: - Apply appropriate methods to describe and present categorical data in summaries, tables and/or graphs.
- Formulate solutions to problems and develop statistical models involving categorical data.
- Program appropriate SAS procedures to produce appropriate graphs, reports, and statistical output.
- Communicate results to others regarding categorical data analysis.
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