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TABLE 14-16
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:
ANOVA
-Referring to Table 14-16, the null hypothesis should be rejected at a 5% level of significance when testing whether daily average of the percentage of students attending class has any effect on percentage of students passing the proficiency test.
Linearly Related
A description of two variables that change at a constant rate with respect to each other.
Late Assignments
Assignments submitted after the deadline.
Annual Income
The total amount of income earned over a year before taxes and other deductions.
Square Foot
A unit of area measurement equal to a square measuring one foot on each side.
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