Statistics 2: ANOVA and Regression
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 9.2 to
- fit polymonial regression models using the REG procedure
- select models based on several statistics and automatic model selection methods using PROC REG
- evaluate model fit and model assumptions using the REG, GLM, GENMOD, and UNIVARIATE procedures
- fit Poisson, negative binomial, and gamma regression models using the GENMOD procedure
- perform analysis of variance using the GLM procedure
- write CONTRAST and ESTIMATE statements in PROC GLM
- fit regression models with dummy variables using PROC REG and ANCOVA models using PROC GLM
- fit models with random effects using the MIXED procedure
- create a variety of statistical graphs.
Who should attend
Data analysts and researchers with some statistical training. Students should have completed the
SAS Programming 1: Essentials and
Statistics I: Introduction to ANOVA, Regression, and Logistic Regression courses, or have equivalent experience.
Duration: 3 days
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 I: Introduction to ANOVA, Regression, and Logistic Regression course.
Regression
- building and evaluating multiple polynomial regression models
- dealing with violations of model assumptions
Analysis of Variance
- performing n-way ANOVA
- interpreting significant interactions
- writing CONTRAST and ESTIMATE statements
- understanding issues associated with unbalanced data
Regression Using Indicator Variables and Analysis of Covariance
- using and interpreting indicator variables in the REG procedure
- building and interpreting analysis of covariance models using the GLM procedure
- comparing regression using indicator variables with analysis of covariance
Generalized Linear Models
- using the GENMOD procedure to fit Poisson, negative binomial, and gamma regression models
Linear Mixed Models
- performing linear mixed model analysis
Students have unlimited 24/7 access to the interactive multimedia course on the Web for one year.
The course requires only a standard Web browser and a free Flash plug-in. The course includes data
that can be downloaded, printable lesson summaries, a Quick Reference Guide, practices and solutions,
step-by-step demonstrations, and a Certificate of Completion.
This course addresses SAS/ETS, SAS/GRAPH, SAS/STAT. You benefit from this course even if SAS/GRAPH software is not installed at your location.
You should
- use Internet Explorer 6.0 or later or Firefox 1.5 or later, with JavaScript and cookies enabled
- have the latest version of Macromedia Flash Player installed
- have base SAS software visible on the same machine that you are taking the training on so that you can practice your new skills in your own SAS environment.
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