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
Section: Chapter Questions
Problem 30PT: For the following exercises, use Table 4 which shows the percent of unemployed persons 25 years or...
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