More Than Just One Predictor – MLR

In Chapter 2, Basic Concepts – Simple Linear Regression, we understood the concept of simple linear regression that covers the relationship between only one independent variable (explanatory variable) and the dependent variable (response variable). It's not very often that we find a variable that depends solely on another. Usually, we find that the response variable depends on at least two predictors.

Let's take a look at an example. Getting to the workplace can often be a path full of variables. Scheduling your departure to arrive on time can be a difficult task. That is why you need to take different variables into account: the distance from your home, the type of route to follow (street type), traffic ...

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