TABLE 13-15
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, = : % Attendance, = Salaries and = Spending:

-Referring to Table 13-15, which of the following is the correct null 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 13-15
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,  = : % Attendance,  = Salaries and  = Spending:
 
-Referring to Table 13-15, which of the following is the correct null 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 null 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 H₀: β₁ = 0. This is because β₁ represents the coefficient associated with the independent variable % Attendance, which is the variable of interest in this hypothesis. The null hypothesis states that this coefficient is equal to zero, implying that % Attendance has no effect on % Passing, once the effect of all other independent variables in the model is accounted for.

TABLE 13-15 the Superintendent of a School District Wanted to Predict the Predict