A statistics teacher was interested in the relationship between the number of days students waited to start a project and the score that project received (out of 100 points). Information was collected on several students and was used to obtain the regression equation ŷ = –3.64x + 96.5, where x represents the number of procrastination days and ŷ is the predicted grade. What is the predicted grade of a student who procrastinated for 2 days?
Answer
A
25.96
B
85.58
C
89.22
D
103.78
Explanation
Substitute x = 2 into the regression equation: ŷ = –3.64(2) + 96.5. This gives ŷ = –7.28 + 96.5 = 89.22. The predicted grade is 89.22, which is choice C.
AI-written and checked against the verified answer.

Question

A statistics teacher was interested in the relationship between the number of days students waited to start a project and the score that project received (out of 100 points). Information was collected on several students and was used to obtain the regression equation ŷ = –3.64x + 96.5, where x represents the number of procrastination days and ŷ is the predicted grade. What is the predicted grade of a student who procrastinated for 2 days?

Answer

A

25.96

B

85.58

C

89.22

D

103.78

Explanation

Substitute x = 2 into the regression equation: ŷ = –3.64(2) + 96.5. This gives ŷ = –7.28 + 96.5 = 89.22. The predicted grade is 89.22, which is choice C.

AI-written and checked against the verified answer.

Revolt · Accepted Answer

89.22

Making Predictions from a Least-Squares Regression Line

Explanation

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