Statistics 2: ANOVA and Regression
STAT2 : ST242
This course teaches you how to analyze continuous response data and discrete count data. Linear regression, Poisson regression, negative binomial regression, gamma regression, analysis of variance, linear regression with indicator variables, analysis of covariance, and mixed models ANOVA are presented in the course.
Learn How To
Use the ODS Graphics facility and the new SG graphical procedures in SAS to:
- Fit polynomial regression models using the GLMSELECT and REG procedures.
- Select models based on several statistics and automatic model selection methods using PROC GLMSELECT.
- Evaluate model fit and model assumptions using the GLMSELECT, REG, GLM, GENMOD, and UNIVARIATE procedures.
- Fit Poisson and negative binomial models using the GENMOD procedure, and fit gamma regression models using the GLIMMIX procedure.
- Perform analysis of variance using the GLM procedure.
- Write LSMESTIMATE statements in PROC GLM.
- Fit ANCOVA models using PROC GLM.
- Fit models with random effects using PROC GLIMMIX.
- Create a variety of statistical graphs.
Who Should Attend
Data analysts and researchers with some statistical training
Prerequisites
Before attending this course, you should:
- Have some experience creating and managing SAS data sets, which you can gain from the SAS Programming 1: Essentials course.
- Be able to fit simple and multiple linear regression models using the REG procedure.
- Be able to analyze a one-way analysis of variance using the GLM procedure.
- Understand the statistical concepts of normal distribution, sampling distributions, hypothesis testing, and estimation.
- Have completed a graduate-level course in regression and analysis of variance methods or the Statistics 1: Introduction to ANOVA, Regression, and Logistic Regression course.
SAS Products Covered
SAS/STAT;SAS/ETS
Course Outline
Multiple Linear Regression
- Review of general linear models.
- Simple polynomial regression.
- Polynomial regression and multicollinearity.
- Modeling nonlinear relationships.
- Regression model diagnostics.
- Remedial measures.
- ANOVA review.
- Postfitting analyses.
- Evaluations of model assumptions and remedial measures.
- Introduction to analysis of covariance (ANCOVA).
- Least squares means for ANCOVA models.
- Diagnostics and remedial measures for ANCOVA models.
- Introduction to generalized linear models.
- Poisson regression and negative binomial regression.
- Introduction to gamma regression.
- Basics of general linear models.
- Fitting linear mixed models.
Live Class Schedule
Duration: 21 hours
Step into our live classes and experience a dynamic learning environment where you can ask questions, share ideas, and connect with your instructor and classmates. With on-demand lab hours, you can explore the material at your own pace. Our globally acclaimed instructors will motivate you to think bigger, so you can take what you've learned and achieve your biggest goals.
This course isn't publicly scheduled, but private training and mentoring may be available. Contact us to explore options.
Private Training
Get training tailored specifically for your team, led by expert SAS instructors. Choose from virtual sessions, or training at your location (or ours). Perfect for teams seeking a customized curriculum and plenty of interaction with a SAS specialist. We'll schedule it at a time that works for you.
Mentoring Services
Take your training to the next level with personalized mentoring. While private training offers structured coursework, mentoring provides hands-on, real-time support from a subject matter expert. As you work with your own data, you'll receive expert guidance to help you uncover insights, unlock the full potential of your data, and make faster progress. Perfect for those looking to apply what they’ve learned and see quicker results.