Use the data to develop a regression model to predict selling price based on the square footage,
number of bedrooms, and age. Use this to predict the selling price of a 10-year-old, 2,000-square-foot house with three bedrooms.
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
174,000 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
1 State the linear equation.
2 Explain the overall statistical significance of the model.
3 Explain the statistical significance for each independent variable in the model
4 Interpret the Adjusted R2.
5 Is this a good predictive equation(s)? Which variables should be excluded (if any) and why? Explain.