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Instruction 13.35 the Education Department's Regional Executive Officer Wanted to Predict the Predict

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Instruction 13.35
The education department's regional executive officer wanted to predict the percentage of students passing a Grade 6 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.
Following is the multiple regression output with Y = % Passing as the dependent variable, X1 = % Attendance, X2 = Salaries and X3 = Spending:
Instruction 13.35 The education department's regional executive officer wanted to predict the percentage of students passing a Grade 6 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. Following is the multiple regression output with Y = % Passing as the dependent variable, X<sub>1</sub> = % Attendance, X<sub>2 </sub>= Salaries and X<sub>3 </sub>= Spending:    -Referring to Instruction 13.35,what is the value of the test statistics when testing whether instructional spending per pupil has any effect on percentage of students passing the proficiency test,taking into account the effect of all the other independent variables?
-Referring to Instruction 13.35,what is the value of the test statistics when testing whether instructional spending per pupil has any effect on percentage of students passing the proficiency test,taking into account the effect of all the other independent variables?

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