Question

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) 104.21*(time) + 113.38. In 11 months you see the actual sales quantity was 380.64. What is the residual? 1) -1248.69 2) 879.05 3) 369.64 )-879.05 5) -369.64 Question 10 (1 point) Suppose that in a certain neighborhood, the cost of a home (in thousands) is proportional to the size of the home in square feet. The regression equation quantifying this relationship is found to be (price) 0.012"(size) +35.06. You look more closely at one of the houses selected. The house is listed as having 2908.515 square feet and is listed at a price of $128.934 (thousand). The residual is 58.972. Interpret this residual in terms of the problem. 1) The square footage is 58.972 square feet less than what we would expect. 2) The price of the house is 128.934 thousand dollars larger than what we would expect. 3) The square footage is 58.972 square feet larger than what we would expect. 4) The price of the house is 58.972 thousand dollars larger than what we would expect 5) The price of the house is 58.972 thousand dollars less than what we would expect.

Answer 1

Ans 9

Residual = Actual - Predicted

= 380.64- [104.21*11+113.38]

4)-879.05