Garis besar topik

  • Stepwise Regression is a statistical method used to select the most significant independent variables in a regression model iteratively. The process involves adding or removing variables one by one based on certain criteria, such as p-value, Adjusted R-squared, or Akaike Information Criterion (AIC). The goal is to find the optimal regression model with the most relevant predictor variables, thus improving the accuracy and interpretability of the model. This method is useful when we have many variables and want to identify the ones that have the most influence on the dependent variable.