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:
-True or False: Referring to Table 14-15,you can conclude definitively that mean teacher salary individually has no impact on the mean percentage of students passing the proficiency test,taking into account the effect of instructional spending per pupil,at a 1% level of significance based solely on but not actually computing the 99% confidence interval estimate for β₁.

Question

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:

-True or False: Referring to Table 14-15,you can conclude definitively that mean teacher salary individually has no impact on the mean percentage of students passing the proficiency test,taking into account the effect of instructional spending per pupil,at a 1% level of significance based solely on but not actually computing the 99% confidence interval estimate for β₁.

Quizplus · Accepted Answer

We cannot definitively conclude that mean teacher salary individually has no impact on the mean percentage of students passing the proficiency test, taking into account the effect of instructional spending per pupil, at a 1% level of significance based solely on but not actually computing the 99% confidence interval estimate for β₁. Just because the p-value for β₁ is less than 0.01 does not mean that the coefficient for β₁ is significantly different from zero when considering the effect of the other variable (Spending). We would need to conduct an overall F-test or examine the confidence intervals for both coefficients to make any definitive conclusions.

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