A professor wants to understand the relationship between students' class attendance (X;) and the grades that the students secure in the final exam (Y;). The professor selects 108 students at random for the experiment. The estimated OLS regression is: Y₁ = 45.23 +1.86X₁, where Ỹ; denotes the predicted value of the grades obtained by the th student and X; denotes the number of classes the student attends. Let B₁Ax represent the predicted change in the test score associated with a small change in the attendance (Ax). Suppose that the professor wants to see the effect of a fall in attendance by 2 days on the test scores. If the standard error of the estimated slope ₁ is 0.85, the 95% confidence interval for B₁ Ax will be: [.). (Round your answers to two decimal places. Enter a minus sign if your answers are negative.)
A professor wants to understand the relationship between students' class attendance (X;) and the grades that the students secure in the final exam (Y;). The professor selects 108 students at random for the experiment. The estimated OLS regression is: Y₁ = 45.23 +1.86X₁, where Ỹ; denotes the predicted value of the grades obtained by the th student and X; denotes the number of classes the student attends. Let B₁Ax represent the predicted change in the test score associated with a small change in the attendance (Ax). Suppose that the professor wants to see the effect of a fall in attendance by 2 days on the test scores. If the standard error of the estimated slope ₁ is 0.85, the 95% confidence interval for B₁ Ax will be: [.). (Round your answers to two decimal places. Enter a minus sign if your answers are negative.)
Chapter4: Linear Functions
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![A professor wants to understand the relationship between students' class attendance (X;) and the grades that the students secure in the final exam (Y;). The professor
selects 108 students at random for the experiment.
The estimated OLS regression is:
Y₁ = 45.23 +1.86X₁,
where Ỹ; denotes the predicted value of the grades obtained by the th student and X; denotes the number of classes the student attends.
Let B₁Ax represent the predicted change in the test score associated with a small change in the attendance (Ax). Suppose that the professor wants to see the effect of
a fall in attendance by 2 days on the test scores.
If the standard error of the estimated slope ₁ is 0.85, the 95% confidence interval for B₁Ax will be: [.].
(Round your answers to two decimal places. Enter a minus sign if your answers are negative.)](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fb90206e9-08b2-4066-9c31-8577660fc164%2Fe741846d-e09a-44e6-a250-3aa56509daa4%2Fua6vr9n_processed.png&w=3840&q=75)
Transcribed Image Text:A professor wants to understand the relationship between students' class attendance (X;) and the grades that the students secure in the final exam (Y;). The professor
selects 108 students at random for the experiment.
The estimated OLS regression is:
Y₁ = 45.23 +1.86X₁,
where Ỹ; denotes the predicted value of the grades obtained by the th student and X; denotes the number of classes the student attends.
Let B₁Ax represent the predicted change in the test score associated with a small change in the attendance (Ax). Suppose that the professor wants to see the effect of
a fall in attendance by 2 days on the test scores.
If the standard error of the estimated slope ₁ is 0.85, the 95% confidence interval for B₁Ax will be: [.].
(Round your answers to two decimal places. Enter a minus sign if your answers are negative.)
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