Create a regression model that is simple ( i. e., does not have too many terms) and still accurately predicts retail price. Validate the model assumptions. Look at residual plots and check for heteroskedasticity, multicollinearity, autocorrelation, and outliers. Your final model should not have significant clusters, skewness, outliers, or heteroskedasticity appearing in the residual plots. Submit your suggested least squares regression formula along with a limited number of appropriate graphs that provide justification for your model. Describe why you believe this model is “best.”