Regression Analysis: Bikes
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From: APPLIED STATISTICS IN
Business and Economics
Doane and Seward
Chapter 13 Section Exercises
13.2 on Page 564
13.4 on Page 566
13.6 on Page 568
13.2 Observations are taken on sales of a certain mountain bike in 30 sporting goods stores. The regression model was Y = total sales (thousands of dollars), X1 = display floor space (square meters), X2 = competitor's advertising expenditures (thousands of dollars), X3 = advertised price (dollars per unit), (a) Write the fitted regression equation. (b) Interpret each coefficient. (c) Would the intercept be likely to have meaning in this regression? (d) Make a prediction for Sales when FloorSpace = 80, CompetingAds = 100, and Price = 1,200. Bikes
13.4 Refer to the ANOVA table for this regression. (a) State the degrees of freedom for the F test for overall significance. (b) Use Appendix F to look up the critical value of F for  = .05. (c) Calculate the F statistic. Is the regression significant overall? (d) Calculate R2 = R2adj, showing your formulas clearly. Bikes
13.6 Observations are taken on sales of a certain mountain bike in 30 sporting goods stores. The regression model was Y = total sales (thousands of dollars), X1 = display floor space (square meters), X2 = competitor's advertising expenditures (thousands of dollars), X3 = advertised price (dollars per unit), X4 = rebate rate (percent of retail price). (a) Calculate the t statistic for each coefficient to test for = 0. (b) Look up the critical value of Student's t in Appendix D for a two-tailed test at = .01. Which coefficients differ significantly from zero? (c) Use Excel to find the p-value for each coefficient. Bikes
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The solution provides step by step method for the calculation of regression analysis. Formula for the calculation and Interpretations of the results are also included.
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