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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 + β1 Size + β2 Age + ε
Model B: Price = β0 + β1 Size + β3 Loc1 + β4 Loc2 + ε
Model C: Price = β0 + β1 Size + β2 Age + 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.
Suppose that at the 10% significance level, you do not reject the null hypothesis, H0: β2 = 0, when testing the significance of Age in Model C. Would you delete Age from Model C?
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