Statistics 2: ANOVA and Regression

Course code: 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.
1 800 EUR

2 178 EUR including VAT

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Course dates

Starting date: Upon request

Type: E-learning

Course duration: 21 hours

Language: en

Price without VAT: 2 070 EUR


Starting date: Upon request

Type: Upon request

Course duration: 21 hours

Language: en

Price without VAT: 1 800 EUR


Type Course
Language Price without VAT
Upon request E-learning 21 hours en 2 070 EUR Register
Upon request Upon request 21 hours en 1 800 EUR Register
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Target group

Data analysts and researchers with some statistical training

Course structure


  • building and evaluating polynomial regression models using PROC GLMSELECT and PROC REG
  • dealing with violations of model assumptions and multicollinearity

Analysis of Variance

  • performing n-way ANOVA
  • interpreting significant interactions
  • writing LSMESTIMATE statements
  • performing evaluation of model assumptions and remedial measures

Regression Using Indicator Variables and Analysis of Covariance

  • building and interpreting analysis of covariance models using the GLM procedure
  • least squares means from an ANCOVA model
  • diagnostics and remedial measures for ANCOVA models

Generalized Linear Models

  • using the GENMOD procedure to fit Poisson and negative binomial regression models
  • using the GLIMMIX procedure to fit gamma regression models

Linear Mixed Models

  • performing linear mixed model analysis with PROC GLIMMIX


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.
  • Do you need advice or a tailor-made course?


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