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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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The hypothalamic-pituitary-adrenal axis, a complex set of direct influences and feedback interactions among the hypothalamus, the pituitary gland, and the adrenal glands, affecting stress response, digestion, immune system, mood and emotions, and energy storage and expenditure.
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