Ch%208_p2 - SUMMARY OUTPUT Regression Statistics Multiple R 0.85 R Square 0.72 Adjusted R Square.69 0 Standard Error 1.14 Observations 11 ANOVA df

Ch%208_p2 - SUMMARY OUTPUT Regression Statistics Multiple R...

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SUMMARY OUTPUT Regression Statistics Multiple R 0.85 R Square 0.72 Adjusted R 0.69 Standard E 1.14 Observation 11 ANOVA df SS MS F Significance F Regression 1 30.11 30.11 23.17 0 Residual 9 11.7 1.3 Total 10 41.81 Coefficients tandard Erro t Stat P-value Lower 95%Upper 95%Lower 95.0% Upper 95.0% Intercept 9.17 1.71 5.35 0 5.3 13.05 5.3 13.05 Sales(10,00 0.01 0 4.81 0 0.01 0.02 0.01 0.02
Ch 8 p2 Page 2 Chapter 8 Problem 2 Year Sales(10,000) Cost(millions) Cost in Year 11 dollars( Price 1 500 $12.00 $16.13 Next year's Unit Sales 2 570 $11.90 $15.53 Next year's revenue 3 610 $11.03 $13.97 Next year's cost 4 650 $13.36 $16.43 Next year's profit 5 720 $14.14 $16.88 Targets tell us 6 750 $13.76 $15.95 5% chance<133 mill 7 790 $14.65 $16.49 5% chance>139 mill 8 870 $18.13 $19.81 9 890 $18.24 $19.35 10 960 $18.24 $18.79 11 990 $20.48 $20.48 Regression for Predicting Future Sales SUMMARY OUTPUT Year t Sales = 462.18+48.73*t+error term error std. dev=11.99 Regression Statistics Multiple R 1 R Square 1 Adjusted R S 0.99 Standard Err 11.99 Observations 11 ANOVA df SS MS F Regression 1 261178.18 261178.18 1815.78 Residual 9 1294.55 143.84 Total 10 262472.73 Coefficients Standard Error t Stat P-value Intercept 462.18 7.76 59.59 0 X Variable 1 48.73 1.14 42.61 0 Regression for Predicting Annual Cost Annual Cost(year 11 millions $s)=

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