Location ID Number Operating Margin Number Nearest Enrollment Income Distance Quality 2801 39.3 3591 2.0 18.5 29 7.6 2608 49.5 2726 1.2 19.0 36 9.3 3191 49.0 2890 2.4 20.0 35 2.6 3210 45.1 2172 1.4 7.0 35 9.2 NNWWW 3701 41.9 3517 2.9 6.0 38 9.1 2547 43.5 2910 1.4 12.5 35 1.8 2670 40.3 2848 2.5 19.0 30 8.4 2664 42.8 3003 2.2 19.5 39 12.0 ANN 2492 57.3 2601 3.1 18.5 39 11.0 2649 52.1 3140 2.2 23.5 34 3.7 3066 25.1 1613 1.7 21.5 29 4.1 2193 54.4 3234 3.2 19.5 39 8.3 2793 47.3 2761 3.4 16.0 39 6.6 3620 57.4 2687 0.9 15.5 42 6.9 2538 NA 38.4 3264 2.7 22.5 29 10.4 3730 56.5 2045 1.5 15.0 38 4.3 3120 35.2 3251 1.7 13.0 35 4.3 2389 39.3 3159 2.7 11.0 34 0.2 3053 WWNH 47.3 2642 1.8 9.0 30 4.8 3304 44.2 3471 2.2 12.0 39 5.4 3770 54.4 2756 3.2 14.5 39 7.9 3380 51.5 3069 3.3 20.5 37 7.7 2795 46.2 2244 3.6 15.5 36 5.9 2315 49.8 2859 1.7 14.5 39 3.0 2682 41.1 3098 2.3 11.5 34 7.7 2789 51.1 3227 1.9 11.0 37 6.0 2847 52.2 2879 2.1 19.5 36 2.9 IWAWNNWWWNWWWA 2372 49.9 3255 2.2 22.5 36 8.7 3349 39.8 3823 3.6 17.0 38 4.8 3704 43.5 3198 1.8 17.0 36 4.6 2872 45.4 2443 0.1 10.5 36 7.5 2570 58.5 2210 2.7 17.5 35 2.7 2956 46.0 2655 1.1 22.0 34 8.1 3098 81.5 4214 2.4 16.0 34 5.6 3256 41.0 3480 1.9 18.0 31 11.0 2486 46.0 2341 2.3 23.0 29 7.4 3466 48.8 2935 3.9 20.0 35 6.1 2912 53.5 3285 2.0 23.5 42 2.9 3200 54.1 2862 2.9 16.5 41 11.8 3208 34.3 3548 2.5 13.5 31 8.3 WWWNNWHWWWWNH 3799 50.2 3021 1.7 8.5 41 5.5 3450 43.3 3383 2.2 11.5 33 9.5 2403 40.8 2676 3.3 25.0 41 5.1 2555 49.0 2826 4.2 17.0 34 1.2 3056 52.0 3354 2.0 26.5 37 7.2 2331 51.2 3082 1.5 22.0 40 11.2\f\fPart 2 (6 marks) Using Minitab or any other statistical software, now perform a multiple linear regression analysis of Operating Margin (response variable) against all the remaining variables as predictors, excluding Location ID Number. a) Write down the regression equation and provide at least two summary measures of the fit of the model. Based on the summary measures, does the model provide a good fit for the data? Explain. b) Plot the residuals against the fitted values and comment on whether the usual model conditions are met. c) The variable Operating Margin New in the dataset corresponds to the Operating Margin variable from which some values have been recorded as missing values. Identify those missing values and explain what they are and why they were recorded as missing. Part 3 (12 marks) Using statistical software, run the same multiple linear regression model as in Part 2 above but this time using Operating Margin New as the response variable. Then, answer the following questions: a) Briefly compare the resulting regression equation and fit with those obtained in Part 2. b) Plot the residuals against the fitted values and comment on whether the model complies with the usual conditions for multiple linear regression. c) Provide an interpretation for the model intercept and for the regression coefficients associated with variables Income and Distance. Is an interpretation of the model intercept appropriate in this case? Compare the value of the regression coefficient for Distance with the one obtained in Part 1 above and clearly explain any difference. d) Do you see any justification for dropping any variable(s) from the model? Explain (hint: multicollinearity; the significance of predictors). e) Run a final model using Operating Margin New as the response variable and including only the significant predictors (hint: those with a p-value s 5%). f) Test the overall significance of the final model in part e). Use a 1% significance level and follow all the steps for hypothesis testing indicated in the Instructions