TABLE 15-4 the Superintendent of a School District Wanted to Predict the Predict

Multiple Choice

TABLE 15-4
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.
Let Y = % Passing as the dependent variable,X₁ = % Attendance,X₂ = Salaries and X₃ = Spending.
The coefficient of multiple determination ( ) of each of the 3 predictors with all the other remaining predictors are,respectively,0.0338,0.4669,and 0.4743.
The output from the best-subset regressions is given below: Following is the residual plot for % Attendance: Following is the output of several multiple regression models:
Model (I) : Model (II) : Model (III) :
-Referring to Table 15-4,the "best" model chosen using the adjusted R-square statistic is

A) X₁,X₃.
B) X₁,X₂,X₃.
C) Either of the above
D) None of the above