Having hands-on experience with multivariate linear regression and collinearity analysis

Simple linear regression is rarely useful because, in reality, many factors will contribute to certain outcomes. We want to increase the complexity of our model to capture more sophisticated one-to-many relationships. In this section, we'll study multivariate linear regression and collinearity analysis.

First, we want to add more terms into the equation as follows:

There is no non-linear term and there are independent variables that contribute to the dependent variable collectively. For example, people's wages can be a dependent variable and their age and number of employment years can be good explanatory/independent variables.

Note on multiple regression and multivariate regression

You may see interchangeable usage of multiple linear regression and multivariate linear regression. Strictly speaking, they are different. Multiple linear regression means that there are multiple...