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

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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, 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, the null hypothesis H₀: β₁ = β₂ = β₃ = 0 implies that percentage of students passing the proficiency test is not affected by any of the explanatory variables. = : % Attendance, 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, the null hypothesis H₀: β₁ = β₂ = β₃ = 0 implies that percentage of students passing the proficiency test is not affected by any of the explanatory variables. = Salaries and 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, the null hypothesis H₀: β₁ = β₂ = β₃ = 0 implies that percentage of students passing the proficiency test is not affected by any of the explanatory variables. = Spending:
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, the null hypothesis H₀: β₁ = β₂ = β₃ = 0 implies that percentage of students passing the proficiency test is not affected by any of the explanatory variables.
-Referring to Table 13-15, the null hypothesis H₀: β₁ = β₂ = β₃ = 0 implies that percentage of students passing the proficiency test is not affected by any of the explanatory variables.


Definitions:

Cumulative Relative Frequency

A measure used in statistics to represent the sum of relative frequencies up to a certain class or level.

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A business that specializes in selling new or used cars at the retail level, typically based on a dealership contract with an automaker or sales subsidiary.

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