Answer each question completely, showing all your work. Copy and Paste the SPSS
ID: 3203894 • Letter: A
Question
Answer each question completely, showing all your work. Copy and Paste the SPSS output into the word document for the calculations portion of the problems. (Please remember to answer the questions you must interpret the SPSS output).
A researcher is interested to learn if there is a linear relationship between the hours in a week spent exercising and a person’s life satisfaction. The researchers collected the following data from a random sample, which included the number of hours spent exercising in a week and a ranking of life satisfaction from 1 to 10 ( 1 being the lowest and 10 the highest).
Participant
Hours of Exercise
Life Satisfaction
1
3
1
2
14
2
3
14
4
4
14
4
5
3
10
6
5
5
7
10
3
8
11
4
9
8
8
10
7
4
11
6
9
12
11
5
13
6
4
14
11
10
15
8
4
16
15
7
17
8
4
18
8
5
19
10
4
20
5
4
Find the mean hours of exercise per week by the participants.
Find the variance of the hours of exercise per week by the participants.
Determine if there is a linear relationship between the hours of exercise per week and the life satisfaction by using the correlation coefficient.
Describe the amount of variation in the life satisfaction ranking that is due to the relationship between the hours of exercise per week and the life satisfaction.
Develop a model of the linear relationship using the regression line formula.
Participant
Hours of Exercise
Life Satisfaction
1
3
1
2
14
2
3
14
4
4
14
4
5
3
10
6
5
5
7
10
3
8
11
4
9
8
8
10
7
4
11
6
9
12
11
5
13
6
4
14
11
10
15
8
4
16
15
7
17
8
4
18
8
5
19
10
4
20
5
4
Explanation / Answer
Result:
Descriptive Statistics
N
Minimum
Maximum
Mean
Std. Deviation
Variance
Hours of Exercise
20
3
15
8.85
3.660
13.397
Life Satisfaction
20
1
10
5.05
2.481
6.155
Valid N (listwise)
20
Find the mean hours of exercise per week by the participants.
Mean =8.85 hours
Find the variance of the hours of exercise per week by the participants.
variance of the hours of exercise =13.397 hours
Determine if there is a linear relationship between the hours of exercise per week and the life satisfaction by using the correlation coefficient.
Correlations
Hours of Exercise
Life Satisfaction
Hours of Exercise
Pearson Correlation
1
-.103
Sig. (2-tailed)
.664
N
20
20
Life Satisfaction
Pearson Correlation
-.103
1
Sig. (2-tailed)
.664
N
20
20
correlation coefficient r= -0.103, P=0.664 which is > 0.05 level.
The correlation is not significant.
Describe the amount of variation in the life satisfaction ranking that is due to the relationship between the hours of exercise per week and the life satisfaction.
Model Summary
Model
R
R Square
Adjusted R Square
Std. Error of the Estimate
1
.103a
.011
-.044
2.535
a. Predictors: (Constant), Hours of Exercise
R square = 0.011
1.1% of variation in the life satisfaction ranking that is due to the relationship between the hours of exercise per week and the life satisfaction.
Develop a model of the linear relationship using the regression line formula.
ANOVAa
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
1.252
1
1.252
.195
.664b
Residual
115.698
18
6.428
Total
116.950
19
a. Dependent Variable: Life Satisfaction
b. Predictors: (Constant), Hours of Exercise
Coefficientsa
Model
Unstandardized Coefficients
Standardized Coefficients
t
Sig.
B
Std. Error
Beta
1
(Constant)
5.671
1.516
3.740
.001
Hours of Exercise
-.070
.159
-.103
-.441
.664
a. Dependent Variable: Life Satisfaction
The regression equation is
Life Satisfaction = 5.671 -0.070* Hours of Exercise
Descriptive Statistics
N
Minimum
Maximum
Mean
Std. Deviation
Variance
Hours of Exercise
20
3
15
8.85
3.660
13.397
Life Satisfaction
20
1
10
5.05
2.481
6.155
Valid N (listwise)
20