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In the following regression model:
ln(HousePrice)=β1+β2Size+β3Bedrooms+u we study the effect of house size and number of bedrooms on the house price.
Based on this regression, how do we assess the effect of the characteristics of the house (both size and number of bedrooms) on the sale price of the house at the 10% significance level?
A. Use a t-test for H0 : β2 = 0 against H0 : β2 ≠ 0 at the 10% significance level, and use a t-test for H0 : β3 = 0 against H0 : β3 ≠ 0 at the 10% level. Reject if at least one of the t-tests rejects.
B. None of the stated options is correct.
C. Use a t-test for H0 : β2 = 0 against H0 : β2 ≠ 0 at 5% level, and use a t-test for H0 : β3 = 0 against H0 : β3 ≠0 at 5% level. Reject if at least one of the t-tests rejects.
D. Use a F-test for the overall significance of the regressors at the 10% significance level.
Consider the following simultaneous equation model where Y1 and Y2 are endogenous variable while X1, X2, X3 and X4 are exogenous variables:
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4 clothing manufacturer tests SRS of 5 specimens of each fabric. Determine the probability that mean breaking strength of 5 untreated specimens exceeds 50 pounds?
From these we calculate = 129.44; = 122.65; sx = 9.15; sy = 11.02. Perform the test H0: against the alternative H1:, using the two sample t-test, and state any assumptions you may require to do this test.
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