A real estate analyst estimates the following regression, relating a house price

Question

A real estate analyst estimates the following regression, relating a house price to its square footage (Saft): Use Table 4 ce = 48.27 + 52.92Sqft, SSE= 56,128; n = 50 In an attempt to improve the results, he adds two more explanatory variables: the number of bedrooms (Beds) and the number of bathrooms (Baths). The estimated regression equation is price = 2862 + 4029sqft + 10.1 7Beds + 1661 Baths, SSE: 48,353; n-60 a. Choose the appropriate hypotheses to determine whether Beds and Baths are jointly significant in explaining Price Ho: 2 = 3 = 0; HA: At least one of the coefficients is nonzero. H0: 2 = 3 = 0; HA: At least one of the coefficients is greater than zero. Ho: 1 = 2 = 3 = 0; HA: At least one of the coefficients is nonzero. b. Calculate the value of the test statistic. (Round intermediate calculations to at least 4 decimal places and final answer to 2 decimal places.) Test statistic C. At the 5% significance level, find the critical value. (Use the appropriate Excel function to calculate the critical value. Round your answer to 2 decimal places) Critical value

Explanation / Answer

Result:

SS due to beds and bath, 56.128-48.353 = 7.775

Df for beds and bath = 2

Df for error = 46

MSS due to beds and bath =7.775/2 =3.8875

MSE= 48.353/46 =1.0511522

Test statistic F = 3.8875/1.0511522 =3.6983227

=3.70 ( two decimals).

Critical value = 1.05

Ho is rejected.

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