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

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True/False

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),mean teacher salary in thousands of dollars (Salaries),and instructional spending per pupil in thousands of dollars (Spending)of 47 schools in the state.
Following is the multiple regression output with Y = % Passing as the dependent variable,X1 = Salaries and X2 = 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),mean teacher salary in thousands of dollars (Salaries),and instructional spending per pupil in thousands of 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>= Salaries and X<sub>2</sub> = Spending:   -True or False: Referring to Table 14-15,you can conclude definitively that instructional spending per pupil individually has no impact on the mean percentage of students passing the proficiency test,taking into account the effect of mean teacher salary,at a 1% level of significance based solely on but not actually computing the 99% the confidence interval estimate for β<sub>2</sub>.
-True or False: Referring to Table 14-15,you can conclude definitively that instructional spending per pupil individually has no impact on the mean percentage of students passing the proficiency test,taking into account the effect of mean teacher salary,at a 1% level of significance based solely on but not actually computing the 99% the confidence interval estimate for β2.

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