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: $\widehat {\text { TestScr }}$ _CA = 681.44 - 0.610×PctLch_CA
_{(0.99)(0.018)}
_n₌_420,_R²⁼^0.75,^SER⁼^9.45 $\widehat {\text { TestScr }}$ _MA = 731.89 - 0.788×PctLch_MA
_{(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?

Question

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:

\widehat {\text { TestScr }}

_CA = 681.44 - 0.610×PctLch_CA
_{(0.99)(0.018)}
_n₌_420,_R²⁼^0.75,^SER⁼^9.45

\widehat {\text { TestScr }}

_MA = 731.89 - 0.788×PctLch_MA
_{(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?

Quizplus · Accepted Answer

The Answer of 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: $\widehat {\text { TestScr }}$ _CA = 681.44 - 0.610×PctLch_CA _{(0.99)(0.018)} _n₌_420,_R²⁼^0.75,^SER⁼^9.45 $\widehat {\text { TestScr }}$ _MA = 731.89 - 0.788×PctLch_MA _{(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?

You Have Read the Analysis in Chapter 9 and Want TestScr ^\widehat {\text { TestScr }} TestScr

You Have Read the Analysis in Chapter 9 and Want $\widehat {\text { TestScr }}$