Question

A)

While attempting to measure its risk exposure for the upcoming year, an insurance company notices a trend between the age of a customer and the number of claims per year. It appears that the number of claims keep going up as customers age. After performing a regression, they find that the relationship is (claims per year) = 0.1*(age) + 5.01. If a customer is 50 years old and they make an average of 9.49 claims per year, what is the residual?

Question 9 options:

	1) 0.52
	2) -40.51
	3) 39.99
	4) -0.52
	5) 40.51

B)

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) = 111.161*(time) + 160.892. In August (time = 8) you see the actual sales quantity was 324.47. The residual is -725.71. Interpret this residual in terms of the problem.

Question 10 options:

	1) The sales is 725.71 units greater than what we would expect.
	2) The sales is 324.47 units less than what we would expect.
	3) The month is 725.71 months larger than what we would expect.
	4) The month is 725.71 months less than what we would expect.
	5) The sales is 725.71 units less than what we would expect.

Answer 1

A)
(claims per year) = 0.1*(age) + 5.01

for age = 50

(claims per year) = 0.1*(50) + 5.01 = 10.01

residual = 9.49 - 10.01 = -0.52

option 4)

B)
(sales) = 111.161*(time) + 160.892

5) The sales is 725.71 units less than what we would expect.