WAGE; = Bo + BLEDUC; + B2EXPER; + B3EXPER? +&i The table below gives the estimated multiple linear regression model. Dependent Variable: WAGE Method: Least Squares Sample: 1 30 Included observations: 30 Variable Coefficient Std. Error t-Statistic Prob. EDUC EXPER EXPER EXPER 4227.660 58.05595 -250.7695 3.877205 9297.600 28.65894 555.3721 8.301464 0.454704 2.025754 -0.451534 0.467051 0.6531 0.0532 0.6553 0.6444 Root MSE Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter. Durbin-Watson stat 348.3611 R-squared 1059.133 Adjusted R-squared 389.6560 S.E. of regression 14.81102 Sum squared resid 14.99785 Log likelihood 14.87079 F-statistic 1.894642 Prob(F-statistic) 0.173163 0.077759 374.1998 3640663 -218.1653 NOT GIVEN NOT GIVEN (a) The multiple regression model provides a method of estimating the effect of EDUC on WAGE, holding labour market experience constant. What does the term "holding labour market experience constant mean? (b) Test, at a = 0.05, the overall utility of the model. If you think there is not enough information given to answer this question, you may write this question cannot be answered on the basis of the information given" as your answer and write down what information you need to answer this