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 + β₁ Size + β₃ Loc1 + β₄ Loc2 + ε
Model C: Price = β₀ + β₁Size + β₂Age + β₃ Loc1 + β₄ Loc2 +ε
where,
Price = the price of a home (in $1,000s)
Size = the square footage (in sq.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.
Using Model B,compute the predicted price of a 2,500-square-foot home in Location 1.

Question

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 + β₁ Size + β₃ Loc1 + β₄ Loc2 + ε
Model C: Price = β₀ + β₁Size + β₂Age + β₃ Loc1 + β₄ Loc2 +ε
where,
Price = the price of a home (in $1,000s)
Size = the square footage (in sq.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.
Using Model B,compute the predicted price of a 2,500-square-foot home in Location 1.

Quizplus · Accepted Answer

The Answer of 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 + β₁ Size + β₃ Loc1 + β₄ Loc2 + ε Model C: Price = β₀ + β₁Size + β₂Age + β₃ Loc1 + β₄ Loc2 +ε where, Price = the price of a home (in $1,000s) Size = the square footage (in sq.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. Using Model B,compute the predicted price of a 2,500-square-foot home in Location 1.

A Realtor Wants to Predict and Compare the Prices of Homes