Question

Abigail gathered data on different schools' winning percentages and the average yearly salary of their head coaches (in millions of dollars) in the years 200020002000-201120112011. She then created the following scatterplot and regression line. The fitted line has a slope of 8.428.428, point, 42. What is the best interpretation of this slope? Choose 1 answer: Choose 1 answer: (Choice A) A A school whose head coach had a salary of \$0$0dollar sign, 0 would have winning percentage of 8.42\%8.42%8, point, 42, percent. (Choice B) B A school whose head coach had a salary of \$0$0dollar sign, 0 would have winning percentage of about 40\%40%40, percent. (Choice C) C On average, each 111 million dollar increase in salary was associated with an 8.428.428, point, 42 point increase in winning percentage. (Choice D) D On average, each 111 point increase in winning percentage was associated with an 8.428.428, point, 42 million dollar increase in salary. A graph plots Winning percentage, from 0 to 100, in increments of 5, versus Salary, in millions of dollars, from 0 to 5, in increments of 0.5. Dozens of points rise diagonally in a loose, wide cluster between (0.3, 22) and (4.1, 83). The cluster is most heavily concentrated leftward of x = 2.5. A regression line rises diagonally through the center of the cluster from (0, 38) to (5.5, 85). All values estimated.

Answer 1

Answer:

  C.  On average, each 1 million dollar increase in salary was associated with an 8.42 point increase in winning percentage

Step-by-step explanation:

Apparently, winning percentage is plotted on the vertical axis, so the slope represents the ratio of winning percentage to salary in millions.

Then an increase in salary by 1 million is expected to be associated with an increase of 8.42 points in winning percentage.