Bundle: Statistics for Business & Economics, Loose-Leaf Version, 13th + MindTap Business Statistics with XLSTAT, 1 term (6 months) Printed Access Card
Bundle: Statistics for Business & Economics, Loose-Leaf Version, 13th + MindTap Business Statistics with XLSTAT, 1 term (6 months) Printed Access Card
13th Edition
ISBN: 9781337148092
Author: David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, Jeffrey D. Camm, James J. Cochran
Publisher: Cengage Learning
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Chapter 16.2, Problem 13E

Refer to exercise 12.

  1. a. Develop an estimated regression equation that can be used to predict the total earnings for all events given the average number of putts taken on greens hit in regulation.
  2. b. Develop an estimated regression equation that can be used to predict the total earnings for all events given the average number of putts taken on greens hit in regulation, the percentage of time a player is able to hit the greens in regulation, and the percentage of times a player’s tee shot comes to rest in the fairway.
  3. c. At the .05 level of significance, test whether the two independent variables added in part (b), the percentage of time a player is able to hit the greens in regulation and the percentage of times a player’s tee shot comes to rest in the fairway, contribute significantly to the estimated regression equation developed in part (a). Explain.
  4. d. In general, lower scores should lead to higher earnings. To investigate this option for predicting total earnings, develop an estimated regression equation that can be used to predict total earnings for all events given the average score for all events. Would you prefer to use this equation to predict total earnings, or would you prefer to use the estimated regression equation developed in part (b)? Explain.
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Use the Financial database from “Excel Databases.xls” on Blackboard.  Use Total Revenues, Total Assets, Return on Equity, Earnings Per Share, Average Yield, and Dividends Per Share to predict the average P/E ratio for a company.  Use Excel to develop the multiple linear regression model.  Assume a 5% level of significance.   Which independent variable is the strongest predictor of the average P/E ratio of a company?     A. Total Revenues B. Average Yield C. Earnings Per Share D.Return on Equity E. Total Assets F.Dividends Per Share   Company Type Total Revenues Total Assets Return on Equity Earnings per Share Average Yield Dividends per Share Average P/E Ratio AFLAC 6 7251 29454 17.1 2.08 0.9 0.22 11.5 Albertson's 4 14690 5219 21.4 2.08 1.6 0.63 19 Allstate 6 20106 80918 20.1 3.56 1 0.36 10.6 Amerada Hess 7 8340 7935 0.2 0.08 1.1 0.6 698.3 American General 6 3362 80620 7.1 2.19 3 1.4 21.2 American Stores 4 19139 8536 12.2 1.01 1.4 0.34 23.5 Amoco 7 36287…

Chapter 16 Solutions

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