(a) Build a multiple regression model for the purposes of predicting calories, using all theother variables as the predictors. (b) Which of the predictors probably does not belong in the model? Explain how you knowthis. What might be your next step after viewing these results? (Hint: use t-test.) (c) Suppose we omit cholesterol from the model and rerun the regression. Explain whatwill happen to the value of R^2. (d) Which predictor is negatively associated with the response? Explain how you knowthis. (Hint: Plot and calculate correlation coefficients) (e) Build a multiple regression model for the purposes of predicting calories, using theforward selection method. (f) Build a multiple regression model for the purposes of predicting calories, using thebackward elimination method. (g) Build a multiple regression model for the purposes of predicting calories, using thestepwise variable selection procedure. (h) Apply the best subsets procedure, and compare against the previous methods. (15 points) (i) Perform all possible regressions. Did the variable selection algorithms find the bestregression? (15 points) ..
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(a) Build a multiple regression model for the purposes of pr
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