Why choosing Stepwise Regression?

This video provides an overview of stepwise regression including its advantages and rationales.

In this video, we explore the principles and advantages of Stepwise Regression, a method used to select variables for inclusion in regression models based on their statistical significance. Learn about the step-by-step approach of Stepwise Regression, which iteratively adds or removes predictors to optimize model fit while controlling for overfitting. Discover how researchers leverage Stepwise Regression to identify the most influential variables in predicting outcomes, streamline model complexity, and improve interpretability. Explore practical examples illustrating the application of Stepwise Regression in different research contexts, from healthcare and economics to social sciences and beyond. Join us as we unravel the methodologies, benefits, and considerations of Stepwise Regression in enhancing predictive accuracy and insights from data analysis

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