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 mean of the percentage of students attending class (% Attendance),mean 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 the most appropriate analysis to perform because it can account for the non-linear relationship between instructional spending per pupil and the percentage of students passing the proficiency test. The superintendent believes that this relationship is positive but decreasing, which suggests a logarithmic function. The log transformation can help to linearize this relationship and make it suitable for regression analysis.

The Superintendent of a School District Wanted to Predict the Percentage