Regression analysis is one of the most widely used techniques for analyzing data. Its broad appeal and usefulness result from the conceptually logical process of using an equation to express the relationship between a variable of interest (the response) and a set of related predictor variables.

The linear regression has five key assumptions:

**Linear relationship**: linear regression needs the relationship between the independent and dependent variables to be linear.**The data is homoskedastic**: meaning the variance in the residuals (the difference in the real and predicted value) is more or less constant.**The residuals are independent**: meaning the residuals are…

MSc in Computer Engineering for Robotics and Smart Industry