# Question

The file P10_08.xlsx contains data on the top 200 professional golfers in each of the years 2003–2009.

a. Create one large data set in a new sheet called All Years that has the data for all seven years stacked on top of one other. In this combined data set, create a new column called Earnings per Round, the ratio of Earnings to Rounds. Similarly, create three other new variables, Eagles per Round, Birdies per Round, and Bogies per Round.

b. Using the data set from part a, run a forward regression of Earnings per Round versus the following potential explanatory variables: Age, Yard/Drive, Driving Accuracy, Greens in Regulation, Putting Average, Sand Save Pct, Eagles per Round, Birdies per Round, and Bogies per Round. Given the results, comment on what seems to be important on the professional tour in terms of earnings per round. For any variable that does not end up in the equation, is it omitted because it is not related to Earnings per Round or because its effect is explained by other variables in the equation?

c. Repeat part b with backward regression. Do you get the same, or basically the same, results?

a. Create one large data set in a new sheet called All Years that has the data for all seven years stacked on top of one other. In this combined data set, create a new column called Earnings per Round, the ratio of Earnings to Rounds. Similarly, create three other new variables, Eagles per Round, Birdies per Round, and Bogies per Round.

b. Using the data set from part a, run a forward regression of Earnings per Round versus the following potential explanatory variables: Age, Yard/Drive, Driving Accuracy, Greens in Regulation, Putting Average, Sand Save Pct, Eagles per Round, Birdies per Round, and Bogies per Round. Given the results, comment on what seems to be important on the professional tour in terms of earnings per round. For any variable that does not end up in the equation, is it omitted because it is not related to Earnings per Round or because its effect is explained by other variables in the equation?

c. Repeat part b with backward regression. Do you get the same, or basically the same, results?

## Answer to relevant Questions

In a study of housing demand, a county assessor is interested in developing a regression model to estimate the selling price of residential properties within her jurisdiction. She randomly selects 15 houses and records the ...The file P02_35.xlsx contains data from a survey of 500 randomly selected households.a. To explain the variation in the size of the Monthly Payment variable, estimate a multiple regression equation that includes the ...The file P10_05.xlsx contains salaries for a sample of DataCom employees, along with several variables that might be related to salary.a. Estimate an appropriate multiple regression equation to predict the annual salary of a ...The belief that larger majorities for a president in a presidential election help the president’s party increase its representation in the House and Senate is called the coattail effect. The file P11_48.xlsx lists the ...A toy company has assigned you to analyze the factors influencing the sales of its most popular doll. The number of these dolls sold during the last 23 years is given in the file P11_57.xlsx. The following factors are ...Post your question

0