Question

Question 7 (1 point)

Zagat restaurant guides publish ratings of restaurants for many large cities around the world. The restaurants are rated on a 0 to 30 point scale based on quality of food, decor, service, and cost. Suppose the regression equation that predicts the cost of dinner using the rating of the quality of food for the restaurants in a particular city is (cost of dinner) = 4.989*(food quality) + 2.406. If a restaurant in the city was given a Zagat rating of 16, what should we expect the cost of dinner to be based on the regression equation?

Question 7 options:

	1) 82.23
	2) We do not know the observations in the data set, so we cannot answer that question.
	3) 2.72
	4) 79.82
	5) 43.48

Question 8 (1 point)

Zagat restaurant guides publish ratings of restaurants for many large cities around the world. The restaurants are rated on a 0 to 30 point scale based on quality of food, decor, service, and cost. Suppose the regression equation that predicts the cost of dinner using the rating of the quality of food for the restaurants in a particular city is (cost of dinner) = 4.896*(food quality) + 2.151. Interpret the slope.

Question 8 options:

	1) When cost of dinner increases by 1 dollar, food quality increases by 2.151 points.
	2) When cost of dinner increases by 1 dollar, food quality increases by 4.896 points.
	3) When food quality increases by 1 point, cost of dinner increases by 2.151 dollars.
	4) When food quality increases by 1 point, cost of dinner increases by 4.896 dollars.
	5) We are not given the dataset, so we cannot make an interpretation.

Question 9 (1 point)

You work for a company in the marketing department. Your manager has tasked you with forecasting sales by month for the next year. You notice that over the past 12 months sales have consistently gone up in a linear fashion, so you decide to run a regression the company's sales history. You find that the regression equation for the data is (sales) = 114.25*(time) + 118.58. In 10 months you see the actual sales quantity was 312.55. What is the residual?

Question 9 options:

	1) 948.53
	2) -1251.08
	3) -948.53
	4) -302.55
	5) 302.55

Question 10 (1 point)

You work for a company in the marketing department. Your manager has tasked you with forecasting sales by month for the next year. You notice that over the past 12 months sales have consistently gone up in a linear fashion, so you decide to run a regression the company's sales history. You find that the regression equation for the data is (sales) = 60.829*(time) + 177.207. In August (time = 8) you see the actual sales quantity was 398.333. The residual is -265.506. Interpret this residual in terms of the problem.

Question 10 options:

	1) The sales is 265.506 units less than what we would expect.
	2) The sales is 265.506 units greater than what we would expect.
	3) The sales is 398.333 units less than what we would expect.
	4) The month is 265.506 months less than what we would expect.
	5) The month is 265.506 months larger than what we would expect.

Answer 1