As one of the most fundamental and widely used methods in planning research, the linear regression is introduced and explained in this chapter. It explains the useful nature of the linear regression, and provides both the purpose and history of the regression tests. The purpose section explains the predictive nature of regression tests, the value in hypothesis testing, as well as a warning on how to use regression wisely. The mechanics section includes the equations for computing regression equations. It also utilizes tables and figures to explain the information. It also includes a section on how to interpret the results; including a section on R-square, the F-statistic, and t-statistics. The step-by-step section leads readers on how to successfully run regressions analyses in SPSS and R. It also provides an overview for assumptions behind the models and problems that may arise from multicollinearity, heteroscedasticity, autocorrelation, nonlinearity, and outliers. The chapter finishes with two brief examples of regression in planning studies.