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You have read the analysis in chapter 9 and want to explore the relationship between poverty and test scores. You decide to start your analysis by running a regression of test scores on the percent of students who are eligible to receive a free/reduced price lunch both in California and in Massachusetts. The results are as follows: CA = 681.44 - 0.610×PctLchCA
(0.99)(0.018)
n = 420, R2 = 0.75, SER = 9.45 MA = 731.89 - 0.788×PctLchMA
(0.95)(0.045)
n = 220, R2 = 0.61, SER = 9.41
Numbers in parenthesis are heteroskedasticity-robust standard errors.
a. Calculate a t-statistic to test whether or not the two slope coefficients are the same.
b. Your textbook compares the slope coefficients for the student-teacher ratio instead of the percent eligible for a free lunch. The authors remark: "Because the two standardized tests are different, the coefficients themselves cannot be compared directly: One point on the Massachusetts test is not the same as one point on the California test." What solution do they suggest?
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