Chapter 4. Understanding and Predicting Data with Linear Regression Models
In this chapter, we are going to see one of the most widely used models in statistics and machine learning: the linear regression model. This model is very useful on its own and also can be considered as a building block of several other methods. If you took a statistics course (even a non-Bayesian one), you may have heard of simple and multiple linear regression, logistic regression, ANOVA, ANCOVA, and so on. All these methods are variations of the same underlying motif, the linear regression model, and this is the main topic of this chapter.
In this chapter, we will cover the following topics:
- Linear regression models
- Simple linear regression
- Robust linear regression
- Hierarchical linear regression
- Polynomial regression
- Multiple linear regression
- Interactions
