Section 2: The multiple linear regression model
• Fit a preliminary model. At this point, do not discuss the regression output.
• Check model assumptions (e.g., constant variance, normality, and uncorrelated errors if
relevant) and diagnostics (outliers, leverage, influence, variance inflation); conduct
Modified-Levene test, test for normality, and Bonferroni outlier test.
IF you have adequate reason, you may remove outliers and re-do the preliminary
• Perform necessary transformations if necessary (check online) and present the
transformed model (remember to re-check model assumptions).
• Clearly present your preliminary model that satisfies the model assumptions.
Section 3: Explore the interaction terms
• Explore interactions using partial regression plots.
• Discuss the addition of possibly useful interaction terms.
• Check correlations involving the added interaction terms before and after standardization.
Section 4: Model search
• Obtain a set of two potentially good models (backwards deletion & stepwise regression):
• Make sure all predictors are significant at the ???? = 0.10 level, and multicollinearity is not a
• Clearly present your potentially good models.