Statistics with SAS
Learn statistical analysis using SAS software, from t-tests and ANOVA to linear and logistic regression. Master practical data analysis skills.
Learn statistical analysis using SAS software, from t-tests and ANOVA to linear and logistic regression. Master practical data analysis skills.
This comprehensive course teaches statistical analysis using SAS/STAT software, focusing on practical applications and interpretations. Students learn fundamental statistical concepts and their implementation in SAS, including hypothesis testing, t-tests, ANOVA, and regression analysis. The curriculum progresses from basic statistical concepts to advanced topics like model selection and categorical data analysis. Through hands-on exercises using SAS software, participants develop skills in data analysis, model building, and statistical inference.
4.7
(292 ratings)
34,383 already enrolled
Instructors:
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What you'll learn
Perform and interpret t-tests and ANOVA analyses
Develop and evaluate linear regression models
Master model selection and validation techniques
Conduct categorical data analysis
Build predictive models using SAS software
Apply statistical inference in practical scenarios
Skills you'll gain
This course includes:
336 Minutes PreRecorded video
61 assignments
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
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There are 8 modules in this course
This SAS-focused statistics course provides comprehensive coverage of statistical analysis techniques through eight detailed modules. The curriculum progresses from fundamental concepts to advanced topics in model building and categorical data analysis. Students learn practical implementation of statistical methods using SAS/STAT software, including t-tests, ANOVA, regression analysis, and logistic regression. The course emphasizes both theoretical understanding and hands-on application.
Course Overview and Data Setup
Module 1 · 36 Minutes to complete
Introduction and Review of Concepts
Module 2 · 2 Hours to complete
ANOVA and Regression
Module 3 · 4 Hours to complete
More Complex Linear Models
Module 4 · 2 Hours to complete
Model Building and Effect Selection
Module 5 · 1 Hours to complete
Model Post-Fitting for Inference
Module 6 · 2 Hours to complete
Model Building for Scoring and Prediction
Module 7 · 1 Hours to complete
Categorical Data Analysis
Module 8 · 4 Hours to complete
Fee Structure
Instructor
Analytical Training Consultant
Jordan Bakerman holds a Ph.D. in statistics from North Carolina State University. His dissertation centered on using social media to forecast real world events, such as civil unrest and influenza rates.
Testimonials
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4.7 course rating
292 ratings
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