6. Professor Worth has analyzed midterm exam scores of students enrolled in his introductory economics course, using data on each student. He has obtained the following regression results: 0.67 + 0.14 SÁT + 0.21 STUDY + 0.07 [STUDY×SAT] + e (0.22) (0.03) SCORE (0.08) (0.02) where entries in parentheses are the standard errors of the parameter estimates immediately above them; SAT the student's SAT score, measured in units of 100 (so a score of 600 has an SAT value of 6, etc.); STUDY = hours that the student spent studying for the midterm; SCORE = the student's score on the midterm; and e = error term. (Note that [STUDY×SAT] is the product of the variables STUDY and SAT.) Ignore possible omitted-variable bias. With this as background, explain what these results tell us about student performance. (Be sure to discuss each of the individual regression coefficients in the above results.)

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ISBN:9781305115545
Author:James Stewart, Lothar Redlin, Saleem Watson
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6. Professor Worth has analyzed midterm exam scores of students enrolled in his introductory
economics course, using data on each student. He has obtained the following regression results:
0.67 + 0.14 SÁT + 0.21 STUDY + 0.07 [STUDY×SAT] + e
(0.22) (0.03)
SCORE
(0.08)
(0.02)
where entries in parentheses are the standard errors of the parameter estimates immediately above them;
SAT
the student's SAT score, measured in units of 100 (so a score of 600 has an SAT value of 6, etc.);
STUDY = hours that the student spent studying for the midterm; SCORE = the student's score on the
midterm; and e = error term. (Note that [STUDY×SAT] is the product of the variables STUDY and
SAT.) Ignore possible omitted-variable bias. With this as background, explain what these results tell us
about student performance. (Be sure to discuss each of the individual regression coefficients in the above
results.)
Transcribed Image Text:6. Professor Worth has analyzed midterm exam scores of students enrolled in his introductory economics course, using data on each student. He has obtained the following regression results: 0.67 + 0.14 SÁT + 0.21 STUDY + 0.07 [STUDY×SAT] + e (0.22) (0.03) SCORE (0.08) (0.02) where entries in parentheses are the standard errors of the parameter estimates immediately above them; SAT the student's SAT score, measured in units of 100 (so a score of 600 has an SAT value of 6, etc.); STUDY = hours that the student spent studying for the midterm; SCORE = the student's score on the midterm; and e = error term. (Note that [STUDY×SAT] is the product of the variables STUDY and SAT.) Ignore possible omitted-variable bias. With this as background, explain what these results tell us about student performance. (Be sure to discuss each of the individual regression coefficients in the above results.)
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