Wal-Mart Revenue: Case Study Two Wal-Mart is the second largest retailer in the world. The data file (WalMart_revenue.xlsx) is included in the Excel data zip file in week one, and it holds monthly data on Wal-Mart's revenue, along with several possibly related economic variables. (a) Develop a multiple linear regression model to predict Wal-Mart revenue, using CPI, Personal Consumption, and Retail Sales Index as the independent variables. (b) Plot the residuals against the predicted values and comment on what you see. (c) Does it seem that Wal-Mart's revenue is closely related to the general state of the economy? Identify and remove the four cases corresponding to December revenue. (d) Develop a multiple linear regression model to predict Wal-Mart revenue, using CPI, Personal Consumption, and Retail Sales Index as the independent variables. (e) Plot the residuals against the predicted values and comment on what you see. (f) Does it seem that Wal-Mart's revenue is closely related to the general state of the economy? (g) Comparing the results of parts (a) and (d), which of these two models is better? Use Rsquare values, adjusted R-square values, Significance F values, p-values and other appropriate criteria to explain your answer. Please use one Excel file to complete this problem, and use one sheet for one sub-problem. Use a Microsoft Word document to answer questions. Finally, upload the file to the submission link for grading. Date 11/28/2003 12/30/2003 1/30/2004 2/27/2004 3/31/2004 4/29/2004 5/28/2004 6/30/2004 7/27/2004 8/27/2004 9/30/2004 10/29/2004 11/29/2004 12/31/2004 1/21/2005 2/24/2005 3/30/2005 4/29/2005 5/25/2005 6/28/2005 7/28/2005 8/26/2005 9/30/2005 10/31/2005 11/28/2005 12/30/2005 1/27/2006 2/23/2006 3/31/2006 4/28/2006 5/25/2006 6/30/2006 7/28/2006 8/29/2006 9/28/2006 10/20/2006 11/24/2006 12/29/2006 1/26/2007 Wal Mart Revenue 14.764 23.106 12.131 13.628 16.722 13.98 14.388 18.111 13.764 14.296 17.169 13.915 15.739 26.177 13.17 15.139 18.683 14.829 15.697 20.23 15.26 15.709 18.618 15.397 17.384 27.92 14.555 18.684 16.639 20.17 16.901 21.47 16.542 16.98 20.091 16.583 18.761 28.795 20.473 CPI 552.7 552.1 554.9 557.9 561.5 563.2 566.4 568.2 567.5 567.6 568.7 571.9 572.2 570.1 571.2 574.5 579 582.9 582.4 582.6 585.2 588.2 595.4 596.7 592 589.4 593.9 595.2 598.6 603.5 606.5 607.8 609.6 610.9 607.9 604.6 603.6 604.5 606.348 Personal Consumption 7868495 7885264 7977730 8005878 8070480 8086579 8196516 8161271 8235349 8246121 8313670 8371605 8410820 8462026 8469443 8520687 8568959 8654352 8644646 8724753 8833907 8825450 8882536 8911627 8916377 8955472 9034368 9079246 9123848 9175181 9238576 9270505 9338876 9352650 9348494 9376027 9410758 9478531 9540335 Retail Sales Index December 301337 0 357704 1 281463 0 282445 0 319107 0 315278 0 328499 0 321151 0 328025 0 326280 0 313444 0 319639 0 324067 0 386918 1 293027 0 294892 0 338969 0 335626 0 345400 0 351068 0 351887 0 355897 0 333652 0 336662 0 344441 0 406510 1 322222 0 318184 0 366989 0 357334 0 380085 0 373279 0 368611 0 382600 0 352686 0 354740 0 363468 0 424946 1 332797 0