Question: Jack Sprague is the relocation specialist for a real estate firm in the town of Arlington, Massachusetts. He has been working with a client who

Jack Sprague is the relocation specialist for a real estate firm in the town of Arlington, Massachusetts. He has been working with a client who wishes to purchase a single-family home in Arlington. After seeing the information that Jack provided, the client is perplexed by the variability of home prices in Arlington. She is especially puzzled by the premium that a colonial house commands. (A colonial house is a style dating back to the time of the American colonies, with a simple rectangular structure and a peaked roof.) Despite Jack’s eloquent explanations, it seems that the client will not be satisfied until she understands the quantitative relationship between house prices and house characteristics. Jack decides to use a multiple regression model to provide the client with the necessary information.

He collects data on the prices for 36 single-family homes in Arlington sold in the first quarter of 2009. Also included in the data is the information on square footage, the number of bedrooms, the number of bathrooms, and whether or not the house is a colonial (1 for colonial; 0 otherwise). A portion of the data is shown in the accompanying table; the entire data set, labeled Arlington_Homes, can be found on the text website.

Price $840,000 822,000 Square feet 2768 2500 Bedrooms 4 4 Baths 3.5


In a report, use the sample information to:

1. Explain why we must include a colonial dummy variable to the list of explanatory variables for explaining home price.

2. Use your preferred model to make predictions for a colonial home versus other styles, given the average values of the explanatory variables.

3. Evaluate the potential problem of changing variability in this model.

Price $840,000 822,000 Square feet 2768 2500 Bedrooms 4 4 Baths 3.5 2.5 Colonial 307,500 850 0

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The regression results for are SUMMARY OUTPUT Regression Statistics Multiple R 08815 R Square 07770 Adjusted R Square 07483 Standard Error 6843534 Obs... View full answer

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