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) autoregressive modeling
B) exponential smoothing
C) least-squares forecasting with monthly or quarterly data
D) Linear regression with log transformation

Question

Quizplus · Accepted Answer

Linear regression with log transformation is appropriate when there is a suspected relationship between predictor and outcome variables that is not linear. The superintendent believes that spending has a positive but decreasing impact on percentage, which suggests a possible logarithmic relationship.

The Superintendent of a School District Wanted to Predict the Percentage