The following output is trom a regression of childrens' years of education on parentstotal years of education and an indicator variable for female (1 if yes, 0 otherwise).SUMMARY OUTPUTRegression StatisticsMultiple RR SquareAdj. R SquareStandard Error0.4910.2410.2172.680Observations100ANOVASignificance F7.23E-06MSRegressionResidual218.562 72.854310.14796689.2787.180Total99 907.840Coefficients8.2640.304StandardError1.0390.1040.130Lower 95% Upper 95%6.2010.097t StatP-valueInterceptFather7.953 3.57E-122.91510.3260.5110.004Mother0.1461.1260.263-0.1120.404Female (1=yes)04510 539 -0.8370.404-1.5210618 If you wanted to test whether the variable of gender has a significant impact on a childs' education what information wouldyou use?Ot-stat = -0.837, p-value = 0.404Ot-stat = 2.915, p-value = .004OF-stat = 10.147, p-value = 7.23E-06Ot-stat = 1.126. p-value = 0.263Othis test cannot be performed with the given informationUsing a step-wise regression to build a model, which variable (if any) would be removed first?O MotherO GenderO FatherOnone would be removedHow many total observations are in this data set?How many independent variables are in this data set?What is the denominator degrees of freedom for the test of the overall significance of the regression?If we removed one of the variables from the model (does not matter which), what are we sure would happen?Owe are sure that R2 will not decreaseOwe are sure that R2 will not increaseOwe are sure that adjusted R2 will not increaseOwe are sure that adjusted R2 will not decreaseOnone of the above

Name: The following output is trom a regression of childrens' years of educ
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Description: The following output is trom a regression of childrens' years of education on parentstotal years of education and an indicator variable for female (1 if yes, 0 otherwise).SUMMARY OUTPUTRegression StatisticsMultiple RR SquareAdj. R SquareStandard Err

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total years of education and an indicator variable for female (1 if yes, 0 otherwise). SUMMARY OUTPUT Regression Statistics Multipie R RSquare Ad. R Square Standard Emor Observations 0.491 0.241 0.217 2.680 100 ANOVA Significance F 7.23-06 SS MS Regression Residual Total 218.562 72.854 10.147 96 689 278 7.180 99 907 840 Standard Emor 1.030 0.104 0.130 t Stat P-value 7.953 3.57E-12 2.915 Coeficients Intercept Father Mother Female (1ayes Lower 95% Upper 95% 6.201 0.097 0.12 8.264 10.326 0.304 0.146 0.511 0.404 0.004 1.126 0.263 0404 0451 0 539 -0837 -1.521 0618

total years of education and an indicator variable for female (1 if yes, 0 otherwise). SUMMARY OUTPUT Regression Statistics Multipie R RSquare Ad. R Square Standard Emor Observations 0.491 0.241 0.217 2.680 100 ANOVA Significance F 7.23-06 SS MS Regression Residual Total 218.562 72.854 10.147 96 689 278 7.180 99 907 840 Standard Emor 1.030 0.104 0.130 t Stat P-value 7.953 3.57E-12 2.915 Coeficients Intercept Father Mother Female (1ayes Lower 95% Upper 95% 6.201 0.097 0.12 8.264 10.326 0.304 0.146 0.511 0.404 0.004 1.126 0.263 0404 0451 0 539 -0837 -1.521 0618

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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