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For example, if Y is annual income ($1000/year), X1 is educational level (number of years of schooling),X2 is number of years of work experience, and X3 is gender (X3 = 0 is male, X3 = 1 is female), then aftera linear regression of the data collected as below:Estimate Std. Error t value Pr(>|t|)(Intercept) 14 7 2 0.031X1 0.6 0.24 2.5 0.011X2 1 0.33 3 0.004X3 1 0.25 4 0.000Residual standard error: 2.7 on 16 degrees of freedomwe assume the estimated parameters are the true values.
Try to answer the questions below:
(a). What is the average difference of annual income between women and men if their otherconditions are the same?
(b). What is the average annual income of a female with 8 years of eduction and 20 years ofworking experience? What about a male of the same condition?
(c). What is the probability that a female with 16 years education and no work experiencewill earn more than $28,000/year?
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Caselet on McDonald’s vs. Burger King - Waiting time
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LINEAR PROGRAMMING MODELS
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