Learners will identify categorical data types, analyze distributions and associations, apply exact tests, construct logistic regression models, and evaluate model performance using SAS. This comprehensive course builds the full skill set needed to work confidently with categorical data across real-world analytical scenarios.

Through hands-on demonstrations, learners gain practical experience generating frequency tables, interpreting crosstabulations, computing Fisher’s Exact p-values, and applying ordinal association techniques. The course then advances into logistic regression, where learners explore odds ratios, probability transformations, model assumptions, effect analysis, and multivariable modeling strategies. Learners also strengthen their predictive analytics skills by using backward elimination, ODS Graphics, honest assessment principles, and data-splitting frameworks. What makes this course unique is its end-to-end coverage of categorical analytics—from foundational concepts to advanced modeling—paired with step-by-step SAS guidance using real examples and interpretable outputs. By the end of the course, learners will be able to design, execute, and validate categorical models with confidence, accuracy, and professional-level competence.