Simple linear regression uses one independent variable to predict one dependent variable. Multiple linear regression uses two or more independent variables to predict a dependent variable.

In the example below, I use an e-commerce data set to build a regression model. I also explain how to determine if the model reveals anything statistically significant, as well as how outliers may ...

You could sift through websites, but some Python code and a little linear regression could make the job easier. ...

Sometimes, a model uses the square, square-root or any other power of one or more independent variables to predict the dependent one, which makes it a non-linear regression.

How Homoskedasticity Works Homoskedasticity is one assumption of linear regression modeling, and data of this type work well with the least squares method.