So far, we have solved simple linear regression problems, which study the relation between the dependent variable *y* and the independent variable *x* based on the regression equation:

In this equation, *x* is the explanatory variable and *y* is the response variable. To solve this problem, we used the least squares method. In this method, the best fitting line can be found by minimizing the sum of the squares of the vertical distance from each data point on the line. In everyday life, it rarely happens that a variable depends solely on another. More often, the response variable depends on at least two predictors. In practice, ...