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Exhibit 17

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Exhibit 17.8.A realtor wants to predict and compare the prices of homes in three neighboring locations.She considers the following linear models:
Model A: Price = β0 + β1Size + β2Age + ε,
Model B: Price = β0 + β1Size + β2Loc1 + β3Loc2 + ε,
Model C: Price = β0 + β1Size + β2Age + β3Loc1 + β4Loc2 + ε,
where,
Price = the price of a home (in $thousands),
Size = the square footage (in square feet),
Loc1 = a dummy variable taking on 1 for Location 1,and 0 otherwise,
Loc2 = a dummy variable taking on 1 for Location 2,and 0 otherwise.
After collecting data on 52 sales and applying regression,her findings were summarized in the following table. Exhibit 17.8.A realtor wants to predict and compare the prices of homes in three neighboring locations.She considers the following linear models: Model A: Price = β<sub>0</sub> + β<sub>1</sub>Size + β<sub>2</sub>Age + ε, Model B: Price = β<sub>0</sub> + β<sub>1</sub>Size + β<sub>2</sub>Loc1 + β<sub>3</sub>Loc2 + ε, Model C: Price = β<sub>0</sub> + β<sub>1</sub>Size + β<sub>2</sub>Age + β<sub>3</sub>Loc1 + β<sub>4</sub>Loc2 + ε, where, Price = the price of a home (in $thousands), Size = the square footage (in square feet), Loc1 = a dummy variable taking on 1 for Location 1,and 0 otherwise, Loc2 = a dummy variable taking on 1 for Location 2,and 0 otherwise. After collecting data on 52 sales and applying regression,her findings were summarized in the following table.   Note: The values of relevant test statistics are shown in parentheses below the estimated coefficients. Refer to Exhibit 17.8.Using Model B,what is the predicted price of a 2,500 square feet home in Location 1? Note: The values of relevant test statistics are shown in parentheses below the estimated coefficients.
Refer to Exhibit 17.8.Using Model B,what is the predicted price of a 2,500 square feet home in Location 1?


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