A Real Estate Analyst Estimates The Following Regression Relating A House Price To Its Square Footage Sqft Price 4 1 (41.82 KiB) Viewed 17 times
A real estate analyst estimates the following regression, relating a house price to its square footage (Sqft): Price = 48.71 +52.35Sqft; SSE= 56,708; 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 = 28.47 +40.77Sqft + 10.10 Beds + 16.14 Baths; SSE = 48,306; n = 50 [You may find it useful to reference the F table.) a. Choose the appropriate hypotheses to determine whether Beds and Baths are jointly significant in explaining Price. HO: B2 = 83 = 0; HA: At least one of the coefficients is greater than zero. HO: 61 = B2 - B3 = 0; HA: At least one of the coefficients is nonzero. OHO: B2 - 63 = 0; HA: At least one of the coefficients is nonzero. b-1. Calculate the value of the test statistic. (Round intermediate calculations to at least 4 decimal places and final answer to 3 decimal places.) Test statistic 4.001
b-2. Find the p-value. O 0.025 s p-value < 0.05 O 0.01 s p-value < 0.025 O p-value < 0.01 O p-value 0.10 O 0.05 s p-value < 0.10 c. At the 5% significance level, what is the conclusion to the test? O Reject Ho Picture Beds and Baths are jointly significant in explaining Price. O Reject Ho Picture Sqft Picture Beds and Baths are jointly significant in explaining Price. Do not reject HolPicture Sqft Picture Beds and Baths are not jointly significant in explaining Price. O Do not reject Ho Picture Beds and Baths are not jointly significant in explaining Price.
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