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TABLE 17-8 the Superintendent of a School District Wanted to Predict the Predict

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TABLE 17-8
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.
Following is the multiple regression output with Y = % Passing as the dependent variable,X1 = % Attendance,X2 = Salaries and X3 = Spending: TABLE 17-8 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. 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:   -True or False: Referring to Table 17-8,you can conclude that the mean teacher salary has no impact on the mean percentage of students passing the proficiency test at a 5% level of significance using the 95% confidence interval estimate for β<sub>2</sub>.
-True or False: Referring to Table 17-8,you can conclude that the mean teacher salary has no impact on the mean percentage of students passing the proficiency test at a 5% level of significance using the 95% confidence interval estimate for β2.

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