A quantitatively savvy, young couple is interested in purchasing a home in southern Sydney. They collected data on 48 houses that had recently sold in the area. They want to predict the selling price of homes (in thousands of dollars) based on the size of the home (in square feet).
The regression equation is House Price (in thousands) = 17.1 + 0.0643 Size (sq. ft.)
Predictor Coef SE Coef T P
Constant 17.06 24.59 0.69 0.491
Size (sq. ft.) 0.06427 0.01224 5.25 0.000
S = 48.5733 R-Sq = 37.5% R-Sq(adj) = 36.1%
Use the computer output to test the slope, at the 5% level, to determine whether size (in square feet) is an effective predictor of the selling price of recently sold homes. Include all details of the test.
a) What are the null (H) and alternative hypotheses (Ha) ?
b) What is the t-test statistics?
c) degree of freedom for this t-test statistics?
d) final conclusion of this test is ?
