What is the main goal of stepwise regression?

• A. To account for all variables without exception
• B. To iteratively add or delete variables based on statistical significance
• C. To improve model accuracy through constant variables
• D. To create a fixed model without adjustments

Answer: (B)

The main goal of stepwise regression is to iteratively add or delete variables based on their statistical significance to identify the most pertinent predictors for the dependent variable being analyzed. This method helps in refining the model by including only those variables that contribute meaningfully to explaining the variance in the outcome being studied.

By evaluating the importance of each variable in a stepwise manner, researchers can enhance the model's comprehensibility and predictive power. This approach not only seeks to optimize the model by balancing complexity and accuracy but also aids in avoiding overfitting by eliminating superfluous variables.

Thus, the iterative nature of stepwise regression, which reflects the statistical significance of variables while forming the model, directly aligns with its primary objective. This characteristic distinguishes it from methodologies that seek to include every variable without consideration for significance, those that aim solely for constant improvements without regard to variable influence, or approaches that create a static model devoid of adjustments.