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.
Virtual Training nebo e-Learning?
Máme dostatečnou flexibilitu, takže vybírat můžete jak prezenční termíny, tak online kurzy.
Zkuste živý kurz virtuálněTarget group
Data analysts and researchers with some statistical training
Course structure
Regression
- 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
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.
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Jsme vám k dispozici na telefonním čísle +420 222 553 101 vždy od pondělí do pátku: 9:00 - 17:00.
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