In a study of housing demand, the county assessor develops the following regression model to estimate the market value (i.e., selling price) of residential property within his jurisdiction. The assessor suspects that important variables affecting selling price (Y, measured in thousands of dollars) are the size of a house (X₁, measured in hundreds of square feet), the total number of rooms (X₂), age (X3), and whether or not the house has an attached garage (X4, No = 0, Yes = 1). Y = a + B₁X₁ + B2X2 + B3X3 + B4X4 + € Now suppose that the estimate of the model produces following results: a = 166.048, b₁ = 3.459, b₂ = 8.015, b3 = -0.319, b4 = 1.186, Sbl = 1.079, Sb2 = 5.288, Sb3 = 0.789, Sb4 = 12.252, R² = 0.838, F-statistic = 12.919, and se = 13.702. Note that the sample consists of 15 randomly selected observations. According to the estimated model, holding all else constant, an additional year in age means the market value increases by approximately Which of the independent variables (if any) appears to be statistically significant (at the 0.05 level) in explaining the market value of residential property? Check all that apply. Size of the house (X₁) Total number of rooms (X₂) Age (X3) Having an attached garage (X4)
In a study of housing demand, the county assessor develops the following regression model to estimate the market value (i.e., selling price) of residential property within his jurisdiction. The assessor suspects that important variables affecting selling price (Y, measured in thousands of dollars) are the size of a house (X₁, measured in hundreds of square feet), the total number of rooms (X₂), age (X3), and whether or not the house has an attached garage (X4, No = 0, Yes = 1). Y = a + B₁X₁ + B2X2 + B3X3 + B4X4 + € Now suppose that the estimate of the model produces following results: a = 166.048, b₁ = 3.459, b₂ = 8.015, b3 = -0.319, b4 = 1.186, Sbl = 1.079, Sb2 = 5.288, Sb3 = 0.789, Sb4 = 12.252, R² = 0.838, F-statistic = 12.919, and se = 13.702. Note that the sample consists of 15 randomly selected observations. According to the estimated model, holding all else constant, an additional year in age means the market value increases by approximately Which of the independent variables (if any) appears to be statistically significant (at the 0.05 level) in explaining the market value of residential property? Check all that apply. Size of the house (X₁) Total number of rooms (X₂) Age (X3) Having an attached garage (X4)
Chapter1: Making Economics Decisions
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Transcribed Image Text:In a study of housing demand, the county assessor develops the following regression model to estimate the market value (i.e., selling price) of
residential property within his jurisdiction. The assessor suspects that important variables affecting selling price (Y, measured in thousands of dollars)
are the size of a house (X₁, measured in hundreds of square feet), the total number of rooms (X₂), age (X3), and whether or not the house has an
attached garage (X4, No = 0, Yes = 1).
Y = a + B₁X₁ + B2X2 + B3X3 + B4X4 + ε
Now suppose that the estimate of the model produces following results: a = 166.048, b₁ = 3.459, b₂ = 8.015, b3 = -0.319, b4 = 1.186,
Sb1 = : 1.079, Sb2 = = 5.288, Sb3 = 0.789, Sb4 = 12.252, R² = 0.838, F-statistic = 12.919, and se = 13.702. Note that the sample consists of 15
randomly selected observations.
According to the estimated model, holding all else constant, an additional year in age means the market value increases
approximately
Which of the independent variables (if any) appears to be statistically significant (at the 0.05 level) in explaining the market value of residential
property? Check all that apply.
00
Size of the house (X₁)
Total number of rooms (X₂)
Age (X3)
by
Having an attached garage (X4)
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