In: Statistics and Probability
2) The following data gives the selling price, square footage, number of bedrooms, and the age of a house in years. These houses have been sold in a specific neighborhood over the last six months.
Selling Price ($) |
Square Footage |
Bedrooms |
Age (years) |
84,000 |
1,670 |
2 |
30 |
79,000 |
1,339 |
2 |
25 |
91,500 |
1,712 |
3 |
30 |
120,000 |
1,840 |
3 |
40 |
127,500 |
2,300 |
3 |
18 |
132,500 |
2,234 |
3 |
30 |
145,000 |
2,311 |
3 |
19 |
164,000 |
2,377 |
3 |
7 |
155,000 |
2,736 |
4 |
10 |
168,000 |
2,500 |
3 |
1 |
172,500 |
2,500 |
4 |
3 |
174,500 |
2,479 |
3 |
3 |
175,000 |
2,400 |
3 |
1 |
177,500 |
3,124 |
4 |
0 |
184,000 |
2,500 |
3 |
2 |
195,500 |
4,062 |
4 |
10 |
195,000 |
2,854 |
3 |
3 |
a) Using square footage develop a model to predict the selling price of the house. How well does the model fit the data? What percentage of the selling price is explained by the model?
b) Using the number of bedrooms develop a model to predict the selling price of the house. How well does the model fit the data? What percentage of the selling price is explained by the model?
c) Using the age of the house develop a model to predict the selling price of the house. How well does the model fit the data? What percentage of the selling price is explained by the model?
d) Which of the models estimated in parts a – d best fits the data? Why did you select that model?