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

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SCENARIO 14-15
The superintendent of a school district wanted to predict the percentage of students passing a sixthgrade 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 X 2 = Spending:
 SCENARIO 14-15 The superintendent of a school district wanted to predict the percentage of students passing a sixthgrade 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, X<sub>1</sub> = Salaries and X <sub>2</sub> = Spending:     -Referring to Scenario 14-15,the null hypothesis H<sub>0</sub>:  \beta <sub>1</sub>= \beta <sub>2</sub>=0implies that percentage of students passing the proficiency test is not related to one of the explanatory variables.
 SCENARIO 14-15 The superintendent of a school district wanted to predict the percentage of students passing a sixthgrade 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, X<sub>1</sub> = Salaries and X <sub>2</sub> = Spending:     -Referring to Scenario 14-15,the null hypothesis H<sub>0</sub>:  \beta <sub>1</sub>= \beta <sub>2</sub>=0implies that percentage of students passing the proficiency test is not related to one of the explanatory variables.
-Referring to Scenario 14-15,the null hypothesis
H0: β\beta 1= β\beta 2=0implies that percentage of
students passing the proficiency test is not related to one of the explanatory variables.


Definitions:

Adjusting Entry

An accounting record made at the end of an accounting period to allocate income and expenditure to the appropriate period.

Weekly Wages

The total amount of earnings paid to an employee or group of employees on a weekly basis.

Factory Personnel

Workers or employees involved in the production processes within a manufacturing facility or plant.

Unearned Ticket Revenue

Income received by a company for goods or services to be delivered or performed in the future; it is considered a liability until the service is performed or goods are delivered.

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