Use the data in MEAP93.RAW to answer this question.
(i) Estimate the model
math10 = β0 + β1 log(expend) + β2lnchprg + u,
and report the results in the usual form, including the sample size and R-squared. Are the signs of the slope coefficients what you expected? Explain.
(ii) What do you make of the intercept you estimated in part (i)? In particular, does it make sense to set the two explanatory variables to zero? [Hint: Recall that log(1)=0.]
(iii) Now run the simple regression of mathlO on log(expend), and compare the slope coefficient with the estimate obtained in part (i). Is the estimated spending effect now larger or smaller than in part (i)?
(iv) Find the correlation between lexpend = log(expend) and lnchprg. Does its sign make sense to you?
(v) Use part (iv) to explain your findings in part (iii).
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