Part II: Using the Generalized Linear Model for many data types.
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4. The General Linear Model I: continuous explanatory variables.
5. The General Linear Model II: categorical explanatory variables.
6. The General Linear Model III: interactions between explanatory variables.
7. One, two and more models fitted to the data: model selection.
8. The Generalized Linear Model.
9.When the response variable is binary.
10.When the response are counts, often with too many zeros.
11. Further issues involved in the modeling of counts.
12. Models for positive, real-valued response variables: proportions and others.
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