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TABLE 14-15 the Superintendent of a School District Wanted to Predict the Predict

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TABLE 14-15
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.
Following is the multiple regression output with Y = % Passing as the dependent variable, X1= % Attendance, X2= Salaries and X3= Spending:
TABLE 14-15 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. 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:    Note:    -Referring to Table 14-15, we can conclude that instructional spending per pupil has no impact on the mean percentage of students passing the proficiency test at a 1% level of significance based solely on the 95% confidence interval estimate for β<sub>3</sub>. Note:
TABLE 14-15 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. 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:    Note:    -Referring to Table 14-15, we can conclude that instructional spending per pupil has no impact on the mean percentage of students passing the proficiency test at a 1% level of significance based solely on the 95% confidence interval estimate for β<sub>3</sub>.
-Referring to Table 14-15, we can conclude that instructional spending per pupil has no impact on the mean percentage of students passing the proficiency test at a 1% level of significance based solely on the 95% confidence interval estimate for β3.


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Compensation systems where employees are paid a set rate for each unit of time worked, calculating earnings based on the number of hours worked at a predetermined rate.

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