Chapter 18 - Chapter 18 18.1 a b 18.2 a 67 b 18.3 a Sales =...

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Unformatted text preview: Chapter 18 18.1 a b 18.2 a 67 b 18.3 a Sales = + 1 Space + 2 Space 2 + b 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 A B C D E F SUMMARY OUTPUT Regression Statistics Multiple R 0.6378 R Square 0.4068 Adjusted R Square 0.3528 Standard Error 41.15 Observations 25 ANOVA df SS MS F Significance F Regression 2 25,540 12,770 7.54 0.0032 Residual 22 37,248 1,693 Total 24 62,788 Coefficients Standard Error t Stat P-value Intercept-108.99 97.24-1.12 0.2744 Space 33.09 8.59 3.85 0.0009 Space-sq-0.666 0.177-3.75 0.0011 s = 41.15 and 2 R = .4068. The model's fit is relatively poor. F = 7.54, p-value = .0032. However, there is enough evidence to support the validity of the model. 18.4a Firstorder model: a Demand = + 1 Price+ Secondorder model: a Demand = + 1 Price + 2 Price 2 + 68 Firstorder model: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 A B C D E F SUMMARY OUTPUT Regression Statistics Multiple R 0.9249 R Square 0.8553 Adjusted R Square 0.8473 Standard Error 13.29 Observations 20 ANOVA df SS MS F Significance F Regression 1 18,798 18,798 106.44 0.0000 Residual 18 3,179 176.6 Total 19 21,977 Coefficients Standard Error t Stat P-value Intercept 453.6 15.18 29.87 0.0000 Price-68.91 6.68-10.32 0.0000 Secondorder model: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 A B C D E F SUMMARY OUTPUT Regression Statistics Multiple R 0.9862 R Square 0.9726 Adjusted R Square 0.9693 Standard Error 5.96 Observations 20 ANOVA df SS MS F Significance F Regression 2 21,374 10,687 301.15 0.0000 Residual 17 603 35.49 Total 19 21,977 Coefficients Standard Error t Stat P-value Intercept 766.9 37.40 20.50 0.0000 Price-359.1 34.19-10.50 0.0000 Price-sq 64.55 7.58 8.52 0.0000 c The second order model fits better because its standard error of estimate is 5.96, whereas that of the first order models is 13.29 d y .= 766.9 359.1(2.95) + 64.55(2.95) 2 = 269.3 69 18.5a Firstorder model: a Time = + 1 Day+ Secondorder model: a Time = + 1 Day + 2 Day 2 + b Firstorder model 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 A B C D E F SUMMARY OUTPUT Regression Statistics Multiple R 0.9222 R Square 0.8504 Adjusted R Square 0.8317 Standard Error 1.79 Observations 10 ANOVA df SS MS F Significance F Regression 1 145.34 145.34 45.48 0.0001 Residual 8 25.56 3.20 Total 9 170.90 Coefficients Standard Error t Stat P-value Intercept 41.40 1.22 33.90 0.0000 Day-1.33 0.197-6.74 0.0001 F = 45.48, p-value = 0. The model is valid. Secondorder model 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 A B C D E F SUMMARY OUTPUT Regression Statistics Multiple R 0.9408 R Square 0.8852 Adjusted R Square 0.8524 Standard Error 1.67 Observations 10 ANOVA df SS MS F Significance F Regression 2 151.28 75.64 26.98 0.0005 Residual 7 19.62 2.80 Total 9 170.90 Coefficients Standard Error t Stat P-value Intercept 43.73 1.97 22.21 0.0000 Day-2.49 0.822-3.03 0.0191 Dat-sq 0.106 0.073 1.46 0.1889 70 F = 26.98, p-value = .0005. The model is valid.F = 26....
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Chapter 18 - Chapter 18 18.1 a b 18.2 a 67 b 18.3 a Sales =...

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