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

question 48

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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) , daily average of the percentage of students attending class (% Attendance) , average 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:
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 average of the percentage of students attending class (% Attendance) , average 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, X<sub>1</sub>= % Attendance, X<sub>2</sub>= Salaries and X<sub>3</sub>= Spending: Note: -Referring to Table 14-15, which of the following is the correct null hypothesis to determine whether there is a significant relationship between percentage of students passing the proficiency test and the entire set of explanatory variables? A) H<sub>0</sub> : β<sub>0</sub> = β<sub>1</sub> = β<sub>2</sub> = β<sub>3</sub> = 0 B) H<sub>0</sub> : β<sub>1</sub> = β<sub>2</sub> = β<sub>3</sub> = 0 C) H<sub>0</sub> : β<sub>0</sub> = β<sub>1</sub> = β<sub>2</sub> = β<sub>3</sub> ≠ 0 D) H<sub>0</sub> : β<sub>1</sub> = β<sub>2</sub> = β<sub>3</sub> ≠ 0 Note:
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 average of the percentage of students attending class (% Attendance) , average 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, X<sub>1</sub>= % Attendance, X<sub>2</sub>= Salaries and X<sub>3</sub>= Spending: Note: -Referring to Table 14-15, which of the following is the correct null hypothesis to determine whether there is a significant relationship between percentage of students passing the proficiency test and the entire set of explanatory variables? A) H<sub>0</sub> : β<sub>0</sub> = β<sub>1</sub> = β<sub>2</sub> = β<sub>3</sub> = 0 B) H<sub>0</sub> : β<sub>1</sub> = β<sub>2</sub> = β<sub>3</sub> = 0 C) H<sub>0</sub> : β<sub>0</sub> = β<sub>1</sub> = β<sub>2</sub> = β<sub>3</sub> ≠ 0 D) H<sub>0</sub> : β<sub>1</sub> = β<sub>2</sub> = β<sub>3</sub> ≠ 0
-Referring to Table 14-15, which of the following is the correct null hypothesis to determine whether there is a significant relationship between percentage of students passing the proficiency test and the entire set of explanatory variables?

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Test Statistic

A calculated value used in statistical testing to determine how far an observed data point is from the expected value under the null hypothesis.

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