BUS 310 HW 9.xlsx - 96 5.0 1.5 90 2.0 2.0 95 4.0 1.5 92 2.5...

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96 5.0 1.5 90 2.0 2.0 95 4.0 1.5 92 2.5 2.5 95 3.0 3.3 94 3.5 2.3 94 2.5 4.2 94 3.0 2.5 A y = 1.6x + 88.64 B y = 1.3x + 2.29x + 83.23 C No, the coefficients are not the same. 59.46% of the variation in weekly gross revenue is explained by the regression. 88.66% of the variation in weekly gross revenue is explained by the regression. D $ 10,438.23 Weekly Gross Revenue ($1000s) Televison Advertising ($1000s) Newspaper Advertising ($1000s)
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SUMMARY OUTPUT Regression Statistics Multiple R 0.8078074081 R Square 0.6525528086 Adjusted R Square 0.5946449433 Standard Error 1.2151751164 Observations 8 ANOVA df SS MS F Significance F Regression 1 16.6400966184 16.640096618 11.268811341 0.015288079 Residual 6 8.8599033816 1.4766505636 Total 7 25.5 Coefficients Standard Error t Stat P-value Lower 95% Intercept 88.637681159 1.5823671313 56.015876091 2.17400E-009 84.765768273 1.6038647343 0.47778079 3.3569050242 0.015288079 0.4347772571 Televison Advertising ($1000s)
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Upper 95% Lower 95.0% Upper 95.0% 92.509594046 84.765768273 92.509594046 2.7729522115 0.4347772571 2.7729522115
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SUMMARY OUTPUT Regression Statistics Multiple R 0.9586634444 R Square 0.9190355997 Adjusted R Square 0.8866498396 Standard Error 0.6425873026 Observations 8 ANOVA df SS MS F Significance F Regression 2 23.4354077925 11.717703896 28.377768388 0.0018652423 Residual 5 2.0645922075 0.4129184415 Total 7 25.5 Coefficients Standard Error t Stat P-value Lower 95% Intercept 83.23009169 1.5738689517 52.882478937 4.57175E-008 79.184332751 2.2901836209 0.3040645561 7.5318993132 0.0006532317 1.5085607963 1.3009890983 0.320701597 4.0566966621 0.0097607978 0.4765993982 15A R-Square: 0.9190355997 91.9% of the variation in weekly gross revenu Adjusted R-Squ 0.8866498396 88.66% of the variation in weekly gross reven 15B Yes, because the percentage of variation is higher.
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