Stepwise regression is an automated tool used in the exploratory stages of model building to identify a useful subset of predictors. The process systematically adds the most significant variable or removes the least significant variable during each step.
For example, an analyst for a real estate consulting firm collects data on home sales for the previous year with the goal of predicting future sales prices. Because the analyst has many potential predictor variables, finding the most significant models could be a time consuming task. Minitab's stepwise regression feature automatically outputs the most significant models along with the R2, adjusted R2, predicted R2, S, and Mallows' Cp to provide a good first step.