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Generalized Linear Models
Not every response variable will be continuous, so a linear regression will not be the correct model in every circumstance. Some outcomes may contain binary data (e.g., sick and not sick), or even count data (e.g., how many heads will I get when I flip a coin). A general class of models called generalized linear models (GLM) can account for these types of data, yet still use a linear combination of predictors.
About This Chapter
This chapter has been improved from its first edition version in a few ways. First, the data set example was changed to use the titanic data set from the seaborn library. The original code from the New York American Community Survey (ACS) was replaced with a new data set to make the model ...
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