12. The OLS estimators of the coefficients in a multivariate linear regression model will be unbiasedand consistent if the following set of conditions holdsA. expected value of the error term given the independent variables is zero, the variance ofthe error term does not depend on the values of the independent variables, theobservations (Yi,Xi,1,X₁,2,...,Xik) are i.i.d., large outliers are unlikelyB. expected value of the error term given the independent variables is zero, the variance ofthe error term does not depend on the values of the independent variables, there is noperfect multicollinearity between the independent variables, the observations(Y₁X₁,1X₁,2,...,Xik) are i.i.d.C. expected value of the error term given the independent variables is zero, there is noperfect multicollinearity between the independent variables, the observations(Yi,Xi,1,Xi,2,...,Xik) are i.i.d., large outliers are unlikelyD. the variance of the error term does not depend on the values of the independentvariables, there is no perfect multicollinearity between the independent variables, theobservations (Yi,X₁,1,X₁,2,...,Xik) are i.i.d., large outliers are unlikely

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Answered: The OLS estimators of the coefficients…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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9)Suppose that Y is normal and we have three explanatory unknowns which are also normal, and we have an independent random sample of 11 members of the population, where for each member, the value of Y as well as the values of the three explanatory unknowns were observed. The data is entered into a computer using linear regression software and the output summary tells us that R-square is 0.79, the linear model coefficient of the first explanatory unknown is 7 with standard error estimate 2.5, the coefficient for the second explanatory unknown is 11 with standard error 2, and the coefficient for the third explanatory unknown is 15 with standard error 4. The regression intercept is reported as 28. The sum of squares in regression (SSR) is reported as 79000 and the sum of squared errors (SSE) is 21000. From this information, what is the adjusted R-square? .8 .7 NONE OF THE OTHERS .6 .5
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