There is an old saying in golf: “You drive for show and you putt for dough.” The

Question

There is an old saying in golf: “You drive for show and you putt for dough.” The point is that good putting is more important than long driving for shooting low scores and hence winning money. To see if this is the case, data on the top 69 money winners on the PGA tour in 1993 are examined. The average number of putts per hole for each player is used to predict the total winnings (in thousands of dollars) using the simple linear regression model

(1993 winnings)i = ?0 + ?1(average number of putts per hole)i + ?i

where the deviations are ?i. This model was fit to the data using the method of least squares. The following results were obtained from statistical software:

R2 = 0.081
s = 281.8

Variable

Parameter estimate

Standard error

Constant or Intercept

7897.2

3023.8

Average putts

–4139.2

1698.4

What is the value of the intercept of the least squares regression line?

–4,139.2

1,698.4

3,023.8

7,897.2

Variable

Parameter estimate

Standard error

Constant or Intercept

7897.2

3023.8

Average putts

–4139.2

1698.4

Explanation / Answer

Solution1:

Regression eq is

winnings=7897.2-4139.2*Average putts

slope=-4139.2

y intercept=7897.2

What is the value of the intercept of the least squares regression line?

7,897.2

OPTION D

Solution2:

From ANOVA output:

F=195.74

p<0.001

P<0.05

Model is significant

OPTIONC

THERE IS A LINEAR RELATIONSHIP BETWEEN CURRENT AND STARTING SALARIES OF THE COMPANY'S EMPLOYEES

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