A real estate analyst estimates the following regression, relating a house price to its square footage (Sqft):

Price= 48.89 + 52.61Sqft; SSE = 56,585; 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= 28.11 + 40.96Sqft + 10.52Beds + 16.76Baths; SSE = 48,387; 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.

H0: 2 = 3 = 0; HA: At least one of the coefficients is greater than zero.

H0: 1 = 2 = 3 = 0; HA: At least one of the coefficients is nonzero.

H0: 2 = 3 = 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.)

What is the Test Statistic_________?

b-2. Find the p-value.

0.025p-value < 0.05

0.01p-value < 0.025

p-value < 0.01

p-value0.10

0.05p-value < 0.10

c. At the 5% significance level, what is the conclusion to the test?

Reject H0Beds and Baths are jointly significant in explaining Price.

Reject H0SqftBeds and Baths are jointly significant in explaining Price.

Do not reject H0SqftBeds and Baths are not jointly significant in explaining Price.

Do not reject H0Beds and Baths are not jointly significant in explaining Price.