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 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:

-Referring to Table 14-15, which of the following is the correct alternative hypothesis to test whether daily mean of the percentage of students attending class has any effect on percentage of students passing the proficiency test, taking into account the effect of all the other independent variables?
A) H₀: = β₀ ≠ 0
B) H₀: = β₁ ≠ 0
C) H₀: = β₂ ≠ 0
D) H₀: = β₃ ≠ 0

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), 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:
 
-Referring to Table 14-15, which of the following is the correct alternative hypothesis to test whether daily mean of the percentage of students attending class has any effect on percentage of students passing the proficiency test, taking into account the effect of all the other independent variables?
A) H₀: = β₀ ≠ 0 
B) H₀: = β₁ ≠ 0 
C) H₀: = β₂ ≠ 0 
D) H₀: = β₃ ≠ 0

Quizplus · Accepted Answer

The alternative hypothesis to test whether daily mean of the percentage of students attending class has any effect on percentage of students passing the proficiency test, taking into account the effect of all the other independent variables, is H₁: β₁ ≠ 0. This is because X₁ represents the daily mean of the percentage of students attending class, which is the variable of interest in the hypothesis, and we want to test whether it has any effect on Y (% Passing) while controlling for the effect of the other independent variables (X₂ and X₃). The null hypothesis H₀ for this test is β₁ = 0, which implies that X₁ has no effect on Y after controlling for the other independent variables.

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