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1. Which is not the assumption of simple linear regression model? a. The value of y for x is :y =β1+β2∗x + eb. The parameter estimate of beta is BLUE c. The variance of random errors Var(e) =σ2d. The variance of random errors cov(e1, e2) = 02.Applying the OLS model y�= 3.41 + 12.89xwhat would the forecast value be when the explanatory variable is 15 a.16.3 b.32.19 c.196.76 d.244.5 3. In the OLS model, what happens to Var(b1)as the sample size N increases? 4. How should b kin the multiple regression model be interpreted? 5. In testing H0: β= cusing 5% significance level, the p-value is 0.38