Exercises T12.4–T12.8 refer to the following setting. An old saying in golf is “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 from a random sample of 69 of the nearly 1000 players on the PGA Tour’s world money list are examined. The average number of putts per hole (fewer is better) and the player’s total winnings for the previous season are recorded and a least-squares regression line was fitted to the data. Assume the conditions for
inference about the slope are met. Here is computer output from the regression analysis:

T12.4 By about how much does the sample slope typically vary from the population slope in repeated random samples of n=69 golfers?
a. 7,897,179
b. 1,698,371
c. 3,023,782
d. 281,777
e. −4,139,198

To determine the sample slope typically vary from the population slope in repeated random samples of $n=69$ golfers.

For shooting low scores and hence winning money, it is assumed that good putting is more significant than long driving.
A random sample of players is picked for analysis to see if this is the fact.
They assumed that the slope inference conditions were met, and that the data was calculated using the computer output provided in the question.
Thus, in the row "Avg. putts" and the column "SE Coef" of the given computer output, the standard error of the slope is presented as:
$S{E}_{b_1}=1698371$
So, the standard error of the slope denotes the average deviation of the sample regression line's slope from the population regression line's slope.
As a result, the slope of the sample regression line differs from the true population regression line by an average of $1698371$.
As a result, option (b)$1698371$is the proper option.