Linear regression model with more than one predictor variable is known as multiple linear regression. For Galton, “regression” referred only to the tendency of extreme data values to “revert” to the overall mean value. Correlation between predictor variables which is also known as factors. %inactivity and %obesity are considered as factors (predictor variable) for %diabetes. A high R-squared value determines how well the model fits in the observed data. Cross Validation is a technique to check error in data and to check overfitting.