Model 1 Coefficients Unstandardized Coefficients B Std. Error (Constant) 37737.496 GPA 5971.460 a. Dependent Variable: Salary 10287.544 2411.927 Standardized Coefficients Beta .350 t 3.668 2.476 Sig. .001 .017 Test the null hypothesis that the population slope is equal to zero against the alternative hypothesis that the population slope is not zero. Conduct the test at the .01 level of significance. State your conclusion and explain how you arrived at that conclusion.
Model 1 Coefficients Unstandardized Coefficients B Std. Error (Constant) 37737.496 GPA 5971.460 a. Dependent Variable: Salary 10287.544 2411.927 Standardized Coefficients Beta .350 t 3.668 2.476 Sig. .001 .017 Test the null hypothesis that the population slope is equal to zero against the alternative hypothesis that the population slope is not zero. Conduct the test at the .01 level of significance. State your conclusion and explain how you arrived at that conclusion.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question

Transcribed Image Text:Does it pay off to study hard at university and graduate with a high grade point average (GPA)? A
researcher has collected data on the GPA (2.0-5.0) and the starting annual salary (in euros) of a
representative sample of 46 graduates from a Business and Management programme. The
researcher used SPSS to fit a simple linear regression model on the data. The SPSS output is shown
below.
Model
1
R Square
122
a. Predictors: (Constant), GPA
Model
1
Model Summary
R
.350
Adjusted R
Square
Sum of
Squares
666314698.9
4782990237
5449304935
Regression
Residual
Total
a. Dependent Variable: Salary
b. Predictors: (Constant), GPA
.102
ANOVA
df
1
44
45
Std. Error of
the Estimate
10426.137
Mean Square
666314698.9
108704323.6
F
6.130
Sig.
.017b

Transcribed Image Text:Model
1
Coefficients
Unstandardized Coefficients
B
Std. Error
(Constant)
37737.496
GPA
5971.460
a. Dependent Variable: Salary
10287.544
2411.927
Standardized
Coefficients
Beta
.350
t
3.668
2.476
Sig.
.001
.017
Test the null hypothesis that the population slope is equal to zero against the alternative hypothesis
that the population slope is not zero. Conduct the test at the .01 level of significance. State your
conclusion and explain how you arrived at that conclusion.
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