Develop a multiple regression model to predict the price of a home based on square footage and location. (Price is in thousands of dollars.) Include a dummy variable to represent the location (1 = on cul-de-sac, 0 = not on cul-de-sac). The first few lines of data are below: Home Price SqFt Cul-de-sac
1 615.6 3055 yes
2 557.4 2731 yes
3 472.6 2515 yes
4 595.3 3011 yes
5 696.9 3267 no
6 409.2 2061 no
7 814.2 3842 no
8 592.4 2777 no
9 695.5 3514 yes
10 495.3 2145 no
11 488.4 2277 no
12 605.4 3200 yes
13 635.7 3065 yes
14 654.8 2998 yes
15 565.6 2875 yes
16 642.2 3000 yes
17 568.9 2374 no
18 686.5 3393 no
19 724.5 3457 yes
20 749.7 3754 yes
What is the interpretation of Ra²?
a. 91.32% of the variation in Price is being explained by the X’s.
b. 91.32% of the variation in Price is being explained by the X’s once we have taken a penalty for the # X’s using.
c. 92.23% of the variation in Price is being explained by the X’s.
d. 92.23% of the variation in Price is being explained by the X’s once we have taken a penalty for the # X’s using.