Chapter 8: Finding the Relationship between Variables

The linear regression algorithm is a supervised machine learning algorithm. We need to train and adjust the linear model before making predictions. We have to understand the data before applying linear regression to be sure that it will be useful for predictions.

You need a certain level of confidence that the variable you want to predict has a relationship with the variables that influence it. If you don't test the extent of this relationship, the predicted values will be errors, and the results will be garbage.

In this chapter, we will learn two methods to test the dependence of the variables to ensure our model's accuracy. We will measure the difference between the expected values from the training dataset and the model's results, and use statistical methods to examine the significance of the relationships between the variables to see whether they are useful for predicting values.

The goal of measuring...