5. The Gauss-Markov theorem will not hold if a. the error term has the same variance given any values of the explanatory variables b. the error term has an expected value of zero given any values of the independent variables c. the independent variables have exact linear relationships among them d. the regression model relies on the method of random sampling for collection of data 6. Which of the following statements is not right? a. The term "linear" in a multiple linear regression model means that the equation is linear in par b. The key assumption for the general multiple regression model is that all factors in the unobser correlated with the explanatory variables. c. The coefficient of determination increases when an independent variable is added to a multipl d. A larger error variance makes it difficult to estimate the partial effect of any of the independer dependent variable. 7. The general t statistic can be written as: Hypothesized value a. t= Standard error b. t = (estimate -hypothesized value) (estimate - hypothesized value) c. t = variance (estimate - hypothesized value) d. t= standard error 8. Which of the following statements is true? a. If the calculated value of F statistic is higher than the critical value, we reject the alternative hyp null hypothesis. b. The F statistic is always nonnegative as SSR, is never smaller than SSR,ur. c. Degrees of freedom of a restricted model is always less than the degrees of freedom of an unre d. The F statistic is more flexible than the t statistic to test a hypothesis with a single restriction. 9. Which of the following cannot cause the usual OLS t statistics to be invalid ? a. Heteroskedasticity b. Omitting an important explanatory variable C. A sample correlation coefficient of 0.95 between two independent variables that are in the moi d. The population error u-Normal(1,o?) 10. Which of the following statements is true? a. If Bi and Bzare the estimated values of regression coefficients associated with two explanatory equation, then the standard error (B1- B2) = standard error (B1)- standard error (B2). b. If the calculated value of the t statistic is greater than the critical value, the null hypothesis, Ho i the alternative hypothesis, H1. c. Standard errors does not have to be positive. d. H: B + 0, where B is a regression coefficient associated with an independent variable, represents hypothesis.