Question: In a study of housing demand, a county assessor is interested in developing a regression model to estimate the selling price of residential properties within her jurisdiction. She randomly selects 15 houses and records the selling price in addition to the following values: the size of the house (in hundreds of square feet), the total number of rooms in the house, the age of the house, and an indication of whether the house has an attached garage. These data are stored in the file P11_26.xlsx.

1. Estimate and thoroughly interpret a multiple regression model that includes the four potential explanatory variables.
2. Evaluate the estimated regression model's goodness of fit.
3. Use the estimated model to predict the sales price of a 3000 -square-foot, 20 -year-old home that has 7 rooms but no attached garage.

Price: $2.99

Solution: The downloadable solution consists of 2 pages
Deliverable: Word Document