In: Statistics and Probability
In Professor Krugman’s economics course, the correlation between the students’ total scores prior to the final exam and their final exam scores is r = 0.7. The pre-final-exam totals for all students in the course have a mean of 265 and a standard deviation of 45. The final exam scores have mean of 76 and standard deviation 9. Professor Krugman has lost Sam’s final exam, but knows that her total before the exam was 290. He decides to predict her final-exam score from her pre-exam total. Use the least-squares best-fit regression line to predict Julie’s final-exam score. Round your answer to one decimal place.
y: Final exam score
x: pre-final-exam total
: Predicted Final exam score
least-squares best-fit regression line
= bo+b1x
Where
Given,
The pre-final-exam totals for all students in the course have a mean of 265 and a standard deviation of 45
i.e
= 265 ; sx = 45
The final exam scores have mean of 76 and standard deviation 9
= 76 ; sy = 9
correlation between the students’ total scores prior to the final exam and their final exam scores is rxy = 0.7
least-squares best-fit regression line
= 38.9+0.14 x
Her total before the exam : x=290
Her predicted final-exam score : is obatined by substituting x: from her pre-exam total= 290 in the regression equation obtained above
= 38.9 + 0.14 x 290 = 38.9+40.6=79.5
Her predicted final-exam score = 79.5