In: Statistics and Probability
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. Develop a linear regression model to predict Wal-Mart revenue, using CPI as the only (a) independent variable. (b) Develop a linear regression model to predict Wal-Mart revenue, using Personal Consumption as the only independent variable. (c) Develop a linear regression model to predict Wal-Mart revenue, using Retail Sales Index as the only independent variable. (d) Which of these three models is the best? Use R-square value, Significance F values and other appropriate criteria to explain your answer. Identify and remove the four cases corresponding to December revenue. (e) Develop a linear regression model to predict Wal-Mart revenue, using CPI as the only independent variable. (f) Develop a linear regression model to predict Wal-Mart revenue, using Personal Consumption as the only independent variable. (g) Develop a linear regression model to predict Wal-Mart revenue, using Retail Sales Index as the only independent variable. (h) Which of these three models is the best? Use R-square values and Significance F values to explain your answer. (i) Comparing the results of parts (d) and (h), which of these two models is better? Use R-square values, Significance F 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 files to the submission link for grading.
| 
 Date  | 
 Wal Mart Revenue  | 
 CPI  | 
 Personal Consumption  | 
 Retail Sales Index  | 
 December  | 
| 
 11/28/03  | 
 14.764  | 
 552.7  | 
 7868495  | 
 301337  | 
 0  | 
| 
 12/30/03  | 
 23.106  | 
 552.1  | 
 7885264  | 
 357704  | 
 1  | 
| 
 1/30/04  | 
 12.131  | 
 554.9  | 
 7977730  | 
 281463  | 
 0  | 
| 
 2/27/04  | 
 13.628  | 
 557.9  | 
 8005878  | 
 282445  | 
 0  | 
| 
 3/31/04  | 
 16.722  | 
 561.5  | 
 8070480  | 
 319107  | 
 0  | 
| 
 4/29/04  | 
 13.98  | 
 563.2  | 
 8086579  | 
 315278  | 
 0  | 
| 
 5/28/04  | 
 14.388  | 
 566.4  | 
 8196516  | 
 328499  | 
 0  | 
| 
 6/30/04  | 
 18.111  | 
 568.2  | 
 8161271  | 
 321151  | 
 0  | 
| 
 7/27/04  | 
 13.764  | 
 567.5  | 
 8235349  | 
 328025  | 
 0  | 
| 
 8/27/04  | 
 14.296  | 
 567.6  | 
 8246121  | 
 326280  | 
 0  | 
| 
 9/30/04  | 
 17.169  | 
 568.7  | 
 8313670  | 
 313444  | 
 0  | 
| 
 10/29/04  | 
 13.915  | 
 571.9  | 
 8371605  | 
 319639  | 
 0  | 
| 
 11/29/04  | 
 15.739  | 
 572.2  | 
 8410820  | 
 324067  | 
 0  | 
| 
 12/31/04  | 
 26.177  | 
 570.1  | 
 8462026  | 
 386918  | 
 1  | 
| 
 1/21/05  | 
 13.17  | 
 571.2  | 
 8469443  | 
 293027  | 
 0  | 
| 
 2/24/05  | 
 15.139  | 
 574.5  | 
 8520687  | 
 294892  | 
 0  | 
| 
 3/30/05  | 
 18.683  | 
 579  | 
 8568959  | 
 338969  | 
 0  | 
| 
 4/29/05  | 
 14.829  | 
 582.9  | 
 8654352  | 
 335626  | 
 0  | 
| 
 5/25/05  | 
 15.697  | 
 582.4  | 
 8644646  | 
 345400  | 
 0  | 
| 
 6/28/05  | 
 20.23  | 
 582.6  | 
 8724753  | 
 351068  | 
 0  | 
| 
 7/28/05  | 
 15.26  | 
 585.2  | 
 8833907  | 
 351887  | 
 0  | 
| 
 8/26/05  | 
 15.709  | 
 588.2  | 
 8825450  | 
 355897  | 
 0  | 
| 
 9/30/05  | 
 18.618  | 
 595.4  | 
 8882536  | 
 333652  | 
 0  | 
| 
 10/31/05  | 
 15.397  | 
 596.7  | 
 8911627  | 
 336662  | 
 0  | 
| 
 11/28/05  | 
 17.384  | 
 592  | 
 8916377  | 
 344441  | 
 0  | 
| 
 12/30/05  | 
 27.92  | 
 589.4  | 
 8955472  | 
 406510  | 
 1  | 
| 
 1/27/06  | 
 14.555  | 
 593.9  | 
 9034368  | 
 322222  | 
 0  | 
| 
 2/23/06  | 
 18.684  | 
 595.2  | 
 9079246  | 
 318184  | 
 0  | 
| 
 3/31/06  | 
 16.639  | 
 598.6  | 
 9123848  | 
 366989  | 
 0  | 
| 
 4/28/06  | 
 20.17  | 
 603.5  | 
 9175181  | 
 357334  | 
 0  | 
| 
 5/25/06  | 
 16.901  | 
 606.5  | 
 9238576  | 
 380085  | 
 0  | 
| 
 6/30/06  | 
 21.47  | 
 607.8  | 
 9270505  | 
 373279  | 
 0  | 
| 
 7/28/06  | 
 16.542  | 
 609.6  | 
 9338876  | 
 368611  | 
 0  | 
| 
 8/29/06  | 
 16.98  | 
 610.9  | 
 9352650  | 
 382600  | 
 0  | 
| 
 9/28/06  | 
 20.091  | 
 607.9  | 
 9348494  | 
 352686  | 
 0  | 
| 
 10/20/06  | 
 16.583  | 
 604.6  | 
 9376027  | 
 354740  | 
 0  | 
| 
 11/24/06  | 
 18.761  | 
 603.6  | 
 9410758  | 
 363468  | 
 0  | 
| 
 12/29/06  | 
 28.795  | 
 604.5  | 
 9478531  | 
 424946  | 
 1  | 
| 
 1/26/07  | 
 20.473  | 
 606.348  | 
 9540335  | 
 332797  | 
 0  | 
Hello Sir/Mam
We are most delighted to answer, but I would request you to please ask atmost 1 question or 4 subparts per posts. Your cooperation is highly appreciated. Thanks!
(a) Linear Regression Model to predict Walmart revenue as CPI as the only independent variable:
y = 1.5834 * x + 556.07
R² = 0.1137

(b) Linear Regression Model to predict Walmart revenue as Personal Consumption as the only independent variable:
y = 0.00004 * x + 273.89
R² = 0.9702

(c) Linear Regression Model to predict Walmart revenue as Retail Sales Index as the only independent variable:
y = 0.0004 * x + 461.49
R² = 0.3969

(d) Using R-Squared Values, it can be concluded that "Personal Consumption" is the best measure to estimate revenue of Walmart as Revenue of Walmart and Personal Consumption are very strongly correlated(R² = 0.9702)(much more than other two measures).
I hope this solves your query.
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