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Part 4: Advanced methods > Generalized linear models

13. Generalized linear models

This chapter covers

  • Formulating a generalized linear model

  • Predicting categorical outcomes

  • Modeling count data


In chapters 8 (regression) and 9 (ANOVA), we explored linear models that can be used to predict a normally distributed response variable from a set of continuous and/or categorical predictor variables. But there are many situations in which it’s unreasonable to assume that the dependent variable is normally distributed (or even continuous). For example:


  

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