DEFINITION of 'Stepwise Regression'

Stepwise regression is the step-by-step iterative construction of a regression model that involves automatic selection of independent variables.

BREAKING DOWN 'Stepwise Regression'

Stepwise regression can be achieved either by trying out one independent variable at a time and including it in the regression model if it is statistically significant, or by including all potential independent variables in the model and eliminating those that are not statistically significant, or by a combination of both methods. Tests for significance are conducted via F-tests, t-tests, adjusted R squared, and a few other less common methods. The goal is to find a set of independent variables which significantly influence the dependent variable. Conducting these tests automatically can potentially save time for the individual.

Drawbacks of Stepwise Regression

Stepwise regression has a number of drawbacks, according to some statisticians. These include incorrect results, an inherent bias in the process itself and the necessity for significant computing power to develop complex regression models through iteration.

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