The county assessor (see Exercise 1) feels that the use of more independent variables in the regression equation might improve the overall explanatory power of the model. In addition to size, the assessor feels that the total number of rooms, age, and whether or not the house has an attached garage might be important variables affecting selling price. The data for the 15 randomly selected dwellings are shown in the following table.

Q1- Which of the independent variables (if any) is statistically significant (at the 0.05 level) in explaining selling price?

1. Size
2. Size, Rooms, Age, and Garage
3. Size and the constant
4. Rooms, Age, and Garage

Q2- What is the approximate 95 percent prediction interval for the selling price of a 15-year-old house having 1,800 sq. ft., 7 rooms, and an attached garage?

1. [153.35 ?minus? 408.17]
2. [266.45 ?minus? 293.56]
3. [253.35 ?minus? 308.17]
4. [353.35 ?minus? 208.17]

Q3- what is the 95 percent prediction interval for the selling price of a house having an area (size) of 15 (hundred) square feet?

1. [247.853 ?minus? 280.147]
2. [136 ?minus? 284.6]
3. [147.853 ?minus? 280.147]
4. [236 ?minus? 284.6]

Q4- Determine the estimated regression line.

1. ?Price space equals space 195.2 space minus 4.34 space Size?
2. ?Price space equals space 4.34 space plus 195.2 space Size
3. ?Size space equals space 195.2 space plus space 4.34 space Price
4. ?Price space equals space 195.2 space plus space 4.34 space Size?

Q5- the t-stat of the independent variable (size) is ___________and the independent variable is ___________.

1. 0.00, significant
2. 9.15, significant
3. 9.15, insignificant
4. 0.00, insignificant

Q6- Using a computer regression program, determine the estimated regression equation with the four explanatory variables shown in the following table.

1. ?Price= 186.63+ 33.8 Size +0.82 space Room+ 0.93 Age - 3.5 Garage?
2. ?Price =33.8 +0.935 space Size + 5.5 Rooms+ 0.79 Age + 11.96 Garage?
3. ?Price =33.8 + 0.935 Size +5.5 Rooms +0.79 Age - 11.96 Garage
4. Price = 186.63 + 33.8 Size + 0.82 Rooms + 0.93 Age + 3.5 Garage?

Q7- What proportion of the total variation in selling price is explained by the regression model?

a- 16.51

b- 0.86

c- 0.81

d-13.71

Observation Selling Price (x Size (x 100 Total No. of $1000) ftz) Age Attached Garage (No= 0, Yes= I Rooms 1) Y X2 265.2 12.0 6 17 0 279.6 20.2 18 0 311.2 27.0 17 328.0 30.0 18 0 0 0 - ON UI A W N A 352.0 30.0 15 281.2 21.4 20 288.4 21.6 8 292.8 25.2 15 H O O O K K O K - - - 356.0 37.2 31 10 236.2 14.4 8 11 272.4 15.0 17 12 291.2 22.4 9 13 299.6 23.9 20 14 307.6 26.6 23 15 320.4 30.7 23