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), mean teacher salar 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, = Salaries and X, = Spending. E Click the icon to view the multiple regression output. Determine whether the following statement is true or false: The null hypothesis Hn: B, = B, = 0 implies that percentage of students passing the proficiency test is not related to one of the explanatory variables. - X Multiple Regression Output O True O False Regression Statistics Multiple R 0.4276 RSquare 0.1828 Adjusted R Square 0.1457 Standard Error 5.7351 Observations 47 ANOVA df Significance F MS Regression 2 323.8284 161.9142 4.9227 0.0118 Residual 44 1447.2094 32.8911 Total 46 1771.0378 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept -72.9916 45.9106 -1.5899 0.1190 -165.5184 19.5352 Salary 2.7939 0.8974 3.1133 0.0032 0.9853 4.6025 Spending 0.3742 0.9782 0.3825 0.7039 -1.5972 2.3455
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), mean teacher salar 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, = Salaries and X, = Spending. E Click the icon to view the multiple regression output. Determine whether the following statement is true or false: The null hypothesis Hn: B, = B, = 0 implies that percentage of students passing the proficiency test is not related to one of the explanatory variables. - X Multiple Regression Output O True O False Regression Statistics Multiple R 0.4276 RSquare 0.1828 Adjusted R Square 0.1457 Standard Error 5.7351 Observations 47 ANOVA df Significance F MS Regression 2 323.8284 161.9142 4.9227 0.0118 Residual 44 1447.2094 32.8911 Total 46 1771.0378 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept -72.9916 45.9106 -1.5899 0.1190 -165.5184 19.5352 Salary 2.7939 0.8974 3.1133 0.0032 0.9853 4.6025 Spending 0.3742 0.9782 0.3825 0.7039 -1.5972 2.3455
Algebra and Trigonometry (MindTap Course List)
4th Edition
ISBN:9781305071742
Author:James Stewart, Lothar Redlin, Saleem Watson
Publisher:James Stewart, Lothar Redlin, Saleem Watson
Chapter1: Equations And Graphs
Section1.FOM: Focus On Modeling: Fitting Lines To Data
Problem 10P
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Transcribed Image Text: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), 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, = Salaries and X, = Spending.
E Click the icon to view the multiple regression output.
Determine whether the following statement is true or false: The null hypothesis Hn: B, = B, = 0 implies that percentage of students passing the proficiency test is not related to one of the explanatory variables.
Multiple Regression Output
True
False
Regression Statistics
Multiple R
0.4276
R Square
0.1828
Adjusted R Square
0.1457
Standard Error
5.7351
Observations
47
ANOVA
df
SS
MS
F
Significance F
Regression
323.8284
161.9142
4.9227
0.0118
Residual
44
1447.2094
32.8911
Total
46
1771.0378
Coefficients
Standard Error
t Stat
P-value
Lower 95%
Upper 95%
Intercept
-72.9916
45,9106
-1.5899
0.1190
-165.5184
19.5352
Salary
2.7939
0.8974
3.1133
0.0032
0.9853
4.6025
Spending
0.3742
0.9782
0.3825
0.7039
-1.5972
2.3455
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