2. Conduct a univariate analysis to test the hypothesis that exposure to stress
ID: 3229263 • Letter: 2
Question
2. Conduct a univariate analysis to test the hypothesis that exposure to stress at work might lead to an increase in body weight in kilograms. Univariate analysis using simple linear regression – Anova Table
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
745.135
1
745.135
4.884
.027
Residual
111829.214
733
152.564
Total
112574.348
734
a. Dependent variable: weight in kgs.
What is the F-ratio? Interpret the value of the F-ratio.
Interpret the significance value for the F-ratio.
What are your conclusions based on the Anova table?
Univariate analysis using simple linear regression – Coefficient Table
Unstandardized Coefficients
Standardized Coefficients
Model
B
Std. Error
Beta
t
Sig.
1
(Constant)
66.204
.784
84.483
.000
Is work stressful
1.168
.528
.081
2.210
.027
What is the beta-coefficient for the intercept in this model?
What is the beta coefficient for work stress?
Interpret the beta coefficient for work stress in relation to body weight.
Interpret the significance value for the beta coefficient for work stress.
Interpret the confidence interval for the beta coefficient for work stress.
Using the Regression Model
By substituting the values from the Coefficients table into the regression equation we can work out the predicted weight for given levels of work stress. For example:
Weight = 0 + 1Stress
= 66.204 + (1.168 x stress)
Work stress is represented by a four category variable (see categories below):
0 = never find the work stressful
1 = occasionally find the work stressful
2 = find work stressful about half the time 3 = find work stressful all the time
What is the predicted value of weight in kilograms for employees who find their work stressful “half the time”?
What is the predicted value of weight in kilograms for employees who find their work stressful “always”
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
745.135
1
745.135
4.884
.027
Residual
111829.214
733
152.564
Total
112574.348
734
Explanation / Answer
Dear student, I am only answering the first 4 subparts as per Chegg Guidelines.
(a) What is the F-ratio? Interpret the value of the F-ratio.
Soln: The F-ratio is 4.884. It means that the ratio of MST to MSE is 4.884
(b) Interpret the significance value for the F-ratio.
Soln: Since the p-value 0.027 is less than 0.05, the F-ratio is signficant at 5% level of significance.
(c) What are your conclusions based on the Anova table?
Soln: Since the F-ratio is significant, the null hypothesis is rejected.
(d) What is the beta-coefficient for the intercept in this model?
SOln: the beta-coefficient for the intercept in this model is 66.204
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