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A researcher developed the following multiple regression model to explain the variation

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Question;A researcher developed the following multiple regression model to explain the variation in hours worked by married women.H =?0 +?1X1 +?2X2 +?3X3 +?4X4 +? Where, H = hours worked per month, X1 = age, X2 = education level, X3 = experience, X4 = husband?s wage,?s = the parameters to be estimate, and? = the error term.All the explanatory variables (age, education level, experience, and husband?s wage) are expected to have negative impact on hours of work.The researcher collected data on H and Xs for a random sample of 428 working women in a given geographical area. Upon estimation of the model, the researcher obtained the following regression output.Explanatory Variable Coefficient Estimate Standard Error of EstimateConstant 1817.334 296.445X1 -16.456 5.365X2 -38.363 16.067X3 49.487 13.734X4 -66.505 12.842Dependent Variable: HoursObservation (n) = 428SSR = 691.8015SST = 1061.8015F-ratio = 16.806a. (8 pts.) Test the statistical significance of the coefficient estimate of each explanatory variable at 5% significance level.b. (3 pts.) Test the statistical significance of the overall;model. c.;(2 pts.) Write the estimatedregression;equation using the coefficient estimates;givenabove. ="msonormal">d.;(2 pts.) Do the experience and the husband?s wage variables have the;expected signs?e. (2 pts.) If the education level increases by 1and;all the other variables do not change, what will happen to the number of hours;worked according to this model?f. (2 pts.)What percent of the variation;in hours worked is explained by this model?="msonormal">="msonormal">="msonormal">

 

Paper#61900 | Written in 18-Jul-2015

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