Suppose you are a potential college student that is interested in determining whether it is worthwhile to declare a certain major.In an effort to find the answer,you collect data on 1,247 college graduates who majored in HUMANITIES,SCIENCE,ENGINEERING,or ENGLISH and you estimate the sample regression function (standard errors in parentheses)

\begin{array} { llllllll } \widehat {\text { Salary }}_{i}=&32,473.81+&5,284.37 \text { GPA }_{4}+&822.56 \text { Male }_{i}+&22,882.43 \text { Science }_{i}\\&( 1,002.97 ) &( 1,323.84 ) & ( 633.85 ) & ( 2,322.43 ) \\\end{array}

\begin{array} { llllllll } &+ 31,136.74 \text { Engineering } _ { i } + &896.11 \text { English } _ { i } \\&( 5,768.41 )&( 643.20 ) \\\end{array}

a)How should you interpret the estimated coefficients for SCIENCE,ENGINEERING,and ENGLISH? Draw a graph and explain.
b)How should you interpret the estimated coefficient for MALE?
c)Are the variables statistical significant at a 5% level?
d)Explain,in as much detail as possible,why the following model is not preferred to the original model.

\begin{aligned}\text { salary }_{i}=&\beta_{0} +\beta_{1} \text { GPA } \\& +\beta_{2} \text { Male }_{i}+\beta_{3} \text { Female }_{i}+\beta_{4} \text { Science }_{i} \\& +\beta_{5} \text { Engineering }_{i}+\beta_{6} \text { English }_{i}\end{aligned}

Semi-Log Regressions

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