The superintendent of a school district wanted to predict the percentage of students passing a sixth-grade proficiency test. She obtained the data on percentage of students passing the proficiency test (% Passing), daily average of the percentage of students attending class (% Attendance), average teacher salary in dollars (Salaries), and instructional spending per pupil in dollars (Spending) of 47 schools in the state. She believed that holding everything else constant, instructional spending per pupil had a positive but decreasing impact on percentage. Which of the following would be the most appropriate analysis to perform?
A) logistic regression
B) autoregressive modeling
C) simple linear regression with log transformation
D) least-squares forecasting with monthly or quarterly data

Question

Quizplus · Accepted Answer

Since the superintendent wants to predict the percentage of students passing a sixth-grade proficiency test based on several factors (attendance, salaries, and instructional spending per pupil), a multiple linear regression would be appropriate. However, the superintendent believes that the impact of instructional spending per pupil on percentage passing is positive but decreasing. This suggests that a log transformation of the instructional spending variable may be necessary to account for the diminishing returns. Therefore, the most appropriate analysis would be a simple linear regression with log transformation.

The Superintendent of a School District Wanted to Predict the Percentage