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.
Mastering Categorical Data Analysis with SAS
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Mastering Categorical Data Analysis with SAS
This course is part of Advanced SAS Programming, Macros & Reporting Specialization
Instructor: EDUCBA
Included with
Gain insight into a topic and learn the fundamentals.
Intermediate level
Recommended experience
1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Analyze categorical data using frequency tables, associations, and exact tests in SAS.
Build and interpret logistic regression models, including odds ratios and multivariable effects.
Evaluate and validate categorical models using diagnostics, graphics, and predictive assessment techniques.
Skills you'll gain
- SAS (Software)
- Advanced Analytics
- Exploratory Data Analysis
- Statistical Analysis
- Data Analysis
- Statistical Hypothesis Testing
- Correlation Analysis
- Statistical Methods
- Descriptive Statistics
- Small Data
- Logistic Regression
- Regression Analysis
- Predictive Analytics
- Statistical Modeling
- Probability & Statistics
- Model Evaluation
Details to know
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Recently updated!
January 2026
Assessments
16 assignments
Taught in English
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This course is part of the Advanced SAS Programming, Macros & Reporting Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 4 modules in this course
This module introduces learners to the essential concepts of categorical data analysis using SAS. It builds foundational skills in identifying categorical variables, exploring their distributions, generating frequency tables, interpreting crosstabulations, and evaluating relationships through association tests. Learners gain the analytical groundwork needed to apply more advanced categorical techniques later in the course.
What's included
10 videos4 assignments
This module equips learners with deeper statistical tools for categorical analysis, including Fisher’s Exact Test, exact p-value computation, ordinal association measures, and advanced use of the SAS FREQ procedure. Learners also explore the importance of custom formatting and rank-based corrections for enhanced analytical clarity and accuracy.
What's included
8 videos4 assignments
This module introduces learners to the core principles of logistic regression, including odds ratios, probability transformations, the logit function, and the assumptions underpinning the modeling process. Learners progress through parameter estimation, reference category specification, and foundational model evaluation, gaining the skills needed to build reliable logistic models.
What's included
13 videos4 assignments
In this module, learners delve into multivariable logistic regression, categorical predictor coding, reference cell techniques, effect analysis, and visual diagnostics using ODS Graphics. The module concludes with advanced model validation practices, including backward elimination, honest assessment principles, data splitting strategies, and the creation of missing indicators.
What's included
14 videos4 assignments
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