Final Exam #7

# Final Exam #7 - 16.42845254 to 27.93693208 SUMMARY OUTPUT...

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SUMMARY OUTPUT Regression Statistics Multiple R 0.91 R Square 0.82 Adjusted R Square 0.78 Standard Error 1.57 Observations 6 ANOVA df SS MS F Significance F Regression 1 46.17 46.17 18.79 0.01 Residual 4 9.83 2.46 Total 5 56 Coefficients Standard Error t Stat P-value Lower 95% Intercept 35.85 4.39 8.16 0 23.65 X Variable 1 -0.09 0.02 -4.34 0.01 -0.15

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Upper 95% Lower 95.0% Upper 95.0% 48.05 23.65 48.05 -0.03 -0.15 -0.03
Title: BUSI 508 Final Exam Author: Taryn Lopez Problem #7 Month Price Sales Estimate Sales March 225 15 14.64 =TREND(\$C\$6:\$C\$11,\$B\$6:\$B\$11, April 250 12 12.29 May 200 18 17 June 175 21 19.36 July 185 16 18.41 August 165 20 20.3 95% Prediction Interval Lower Limit Upper Limit Prediction 145 ? 22.18 16.43 27.94 SE 1.57 =B43 SPE 2.07 =B15*SQRT(1+1/6+(B14-AVERAGE(B6:B12)) ^2/(6*VARP(B6:B12))) t 2.78 =TINV(1-0.95,4) C. What is the linear regression model for this data? model to be better it needs to be closer to 100%. The closer to 100% the more accurate the regression model w F. What is the 95% confidence interval for the estimate at \$145?

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Unformatted text preview: 16.42845254 to 27.93693208 SUMMARY OUTPUT Regression Statistics Multiple R 0.91 R Square 0.82 Adjusted R Square 0.78 Standard Error 1.57 Observations 6 ANOVA df SS MS Regression 1 46.17 46.17 Residual 4 9.83 2.46 Total 5 56 Coefficients Standard Error t Stat Upper 95% A. What is the dependent variable? Sales B. What is the independent variable? Price D. If a price of \$145 is proposed, what is the estimate of the sales? 22.18269231 E. How 'good' is the regression model? R2 = .8245. this means the regression model is okay, but for a reg 160170180190200210220230240250260 5 10 15 20 25 f(x) = -0.09x + 35.85 R² = 0.82 Column C Linear Re-gression for Column C Price Sales Intercept 35.85 4.39 8.16 48.05 X Variable 1-0.09 0.02-4.34-0.03 ,B6) will be. ression...
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Final Exam #7 - 16.42845254 to 27.93693208 SUMMARY OUTPUT...

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