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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),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,the null hypothesis should be rejected at a 5% level of significance when testing whether mean teacher salary has any effect on percentage of students passing the proficiency test,taking into account the effect of instructional spending per pupil.
-True or False: Referring to Table 14-15,the null hypothesis should be rejected at a 5% level of significance when testing whether mean teacher salary has any effect on percentage of students passing the proficiency test,taking into account the effect of instructional spending per pupil.

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