What are the benefits and drawbacks of using stepwise methods for variable selection in multiple regression?
Multiple regression is a powerful statistical technique that allows you to analyze the relationship between a dependent variable and several independent variables. However, it also comes with some challenges and limitations, especially when it comes to selecting the best set of predictors. In this article, you will learn about the advantages and disadvantages of multiple regression, and how stepwise methods can help you choose the most relevant variables for your model.