SCENARIO 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, Attendance, Salaries and 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:
-Referring to Scenario 15-4, the "best" model chosen using the adjusted R-square statistic is
C)either of the above
D)None of the above

Question

SCENARIO 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,  Attendance,  Salaries and  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:   
-Referring to Scenario 15-4, the "best" model chosen using the adjusted R-square statistic is
C)either of the above 
D)None of the above

Quizplus · Accepted Answer

The Answer of SCENARIO 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,  Attendance,  Salaries and  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:   
-Referring to Scenario 15-4, the "best" model chosen using the adjusted R-square statistic is
C)either of the above 
D)None of the above

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