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1) Perform the regression and write the estimated regression equation. Do the coefficient signs agree with your a prior expectations? (Round your answers to 4

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Perform the regression and write the estimated regression equation. Do the coefficient signs agree with your a prior expectations? (Round your answers to 4 decimal places.) A picture Click here for the Excel Data Set A Mileage and Other Characteristics of Randomly Selected Vehicles (n = 73, * = 4) Obs Vehicle CityMPG Length Width Weight Man Tran Acura TL 20 109.3 74.0 3968 2 Audi A5 22 108.3 73.0 3583 BMW 4 Series 428i 22 182. 6 71.9 3470 71 Volkswagen Passat SE 24 191. 6 72.2 3230 72 Volvo S60 T5 21 182.2 73.4 3528 73 Volvo XC90 16 189.3 76.2 4667 length - Weight - Man TranRefer to the ANOVA table for this regression. Source d.r. 3 1, 154,410 301,103 20 371,132 14,590 Total 1, 519,742 Click here for the Excel Data File (a) State the degrees of freedom for the Ftest for overall significance. The dogions of freedom for regression ard arid for offor (bj Use Appendix F to look up the critical value of Ffor a= 05. (Round your answer to 2 decimal places.) (c.1) Calculate the /statistic. (Round your answer to 3 decimal places.] Fulatislic (c 2) The overall regression is significant. O No (c.3) The hypotheses are a. H,: All the coefficients are zero (8, = 82 = 8, = 0) vs. My: At least one coefficient is not zero. b. H: At least one coefficient is non-zero vs. H: All the coefficients are zero (8, = 8, = 8, = 0) Ob (d) Calculate R and Red;. (Round your answers to 4 decimal places.)Bikes .XLSX File Edit View Insert Format Data Tools Help Last edit was seconds ago Reload to allow offline editing. Reload 100% % .0_ .00 123 - Default (Ari... 10 BIS A A1 fx A B C D E F G H J K 1 Mountain Bike Sales (n = 30 stores) A W N Obs Sales FloorSpace CompetingAds Price 1015 72.9 102.2 146 903 56.6 99.6 1261 1293 80.4 107.1 1408 NO UA W N - 1479 93.4 110.1 729 1413 84.5 93.5 1227 9 1207 69.8 95.6 966 999 77.4 102.5 1400 00 1172 75.3 94.8 1277 1110 75.5 101.0 1137 10 1270 63.6 95.5 954 11 1448 84.5 100.0 856 12 1327 74.6 110.4 392 Variable Names: Sales = total sales (thousands of 13 910 60.4 98.2 1024 dollars), FloorSpace = display floor space (square 14 455 8.2 86.1 1028 meters), CompetingAds = competitors' advertising 15 1052 48.6 86.3 1170 expenditures (thousands of dollars), Price = 19 16 1125 49.6 94.7 984 advertised price (dollars per unit). 20 17 915 57.4 96.5 1200 21 18 1079 48.5 90.6 1725 22 19 1493 102.1 89.6 1588 23 20 385 55.2 101.1 1298 24 21 1069 56.0 96.8 1359 25 22 1220 76.8 99.8 1469 26 23 1124 59.2 111.1 480 27 24 1043 49.0 94.0 1435 28 25 1369 78.5 99.7 323 29 26 1244 59.4 98.2 1274 30 27 1361 100.0 104.7 1165 31 28 1421 76.3 85.5 1054 32 29 782 41.8 92.5 860 33 30 1210 65.2 93.1 895 34 35Refrigerator prices are affected by characteristics such as whether or not the refrigerator is on sale, whether or not it is listed as a Sub- Zero brand, the number of doors (one door or two doors), and the placement of the freezer compartment (top, side, or bottom). The table below shows the regression output from a regression model using the natural log of price as the dependent variable. The model was developed by the Bureau of Labor Statistics. Standard Variable Coefficient Error t Statistic Intercept 5 . 4841 0. 13081 41.92 Sale price -0 . 0733 0 . 0234 -3. 13 Sub-zero brand 1. 1196 0 . 1462 7 . 66 Total capacity (in cubic feet) 0 . 06956 0 . 005351 13.00 Two-door, freezer on bottom 0 . 04657 0 . 08085 0. 58 Two-door, side freezer Base Two-door, freezer on top -0. 3432 0 . 03596 -9.55 One door with freezer -0 . 7096 0 . 1310 -5.42 One door, no freezer -0 . 8820 0 . 1491 -5.92 (a) Write the regression model, being careful to exclude the base indicator variable. (Negative amounts should be indicated by a minus sign. Round your answers to 4 decimal places.) Answer is complete and correct. In (Price) = 5.4841 + -0.0733 SalePrice + 1.1196 Sub-Zero + 0.0696 Capacity + 0.0466 2DoorFzBot + -0.3432 2DoorFzTop + -0.7096 1DoorFz + -0.8820 1DoorNoFz (b) Find the p-value for each coefficient, using 319 degrees of freedom. Using an a = .01, which predictor variable(s) are not significant predictors? (Leave no cells blank - be certain to enter "0" wherever required. Round your answers to 4 decimal places.) x Answer is not complete. p-value SalePrice 0.0019 Sub-Zero Capacity 2DoorFzBot 2DoorFz Top 1DoorFz 1 DoorNoFz

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