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The next three questions (7 to 9) refer to the following:

We would like to determine how the weight of a car can be used to predict its fuel efficiency. The weight (in pounds) and the fuel efficiency (in miles per gallon) are recorded for a sample of ten cars. The least squares regression line is calculated to be ŷ =51.47−0.0089x{"version":"1.1","math":"\hat{y} = 51.47 - 0.0089x"}. It is also determined that 58.5% of the variation in a car's fuel efficiency can be accounted for by its regression on the car's weight.

Question 7 (1 point)

Question 7 options:

The value of the correlation between weight and fuel efficiency for this sample of cars is:

(Round your answer to 2 decimal places. Ignore the spell check icon.)

Question 8 (1 point)

Which of the following is the correct interpretation of the slope of the least-squares regression line?

Question 8 options:

	A) For every decrease in fuel efficiency by 0.0089 miles per gallon, we predict a car's weight to increase by 1 pound.
	B) For every 1 pound increase in a car's weight, we predict fuel efficiency to decrease by 0.0089 miles per gallon.
	C) For every 0.0089 pound decrease in a car's weight, we predict fuel efficiency to increase by 1 mile per gallon.
	D) For every 1 pound increase in a car's weight, we predict fuel efficiency to increase by 0.0089 miles per gallon.
	E) For every 1 extra mile per gallon in fuel efficiency, we predict a car's weight to decrease by 0.0089 pounds.

Question 9 (1 point)

One car in the sample weighs 4,000 pounds and has a fuel efficiency of 20 miles per gallon. What is the value of the residual for this car?

Report your answer to 2 decimal places.

Your Answer:

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Scores of a Canadian judge (X) and an American judge (Y) are recorded at an international gymnastics competition for a sample of gymnasts. The correlation between X and Y is calculated to be r = 0.9. What is the correct interpretation of this correlation?Question 10 (1 point)

Question 10 options:

	A) There is a strong positive linear relationship between the two judges' scores.
	B) The Canadian judge's scores are, on average, only 90% of the American judge's scores.
	C) The two judges give the same score 90% of the time.
	D) The American judge's scores are, on average, only 90% of the Canadian judge's scores.
	E) When the Canadian judge's score increases by 1, we predict the American judge's score to increase by 0.9.

Answer 1