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***Must be calculated in SPSS*** A researcher is interested to learn if there is

ID: 3300925 • Letter: #

Question

***Must be calculated in SPSS***

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

a. Find the mean hours of exercise per week by the participants.

b. Find the variance of the hours of exercise per week by the participants.

c. Determine if there is a linear relationship between the hours of exercise per week and the life satisfaction by using the correlation coefficient.

d. 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.

e. 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

(***Must be calculated in SPSS***)

a. Find the mean hours of exercise per week by the participants.

Answer:

The mean hours of exercise per week by the participants is given as 8.85.

Required SPSS output is given as below:

Descriptive Statistics

Mean

Std. Deviation

N

Life Satisfaction

5.0500

2.48098

20

Hours of exercise

8.8500

3.66024

20

b. Find the variance of the hours of exercise per week by the participants.

Answer:

From the above output, we have given standard deviation for hours of exercise as 3.66024.

So, required variance = 3.66024^2 = 13.39736

c. Determine if there is a linear relationship between the hours of exercise per week and the life satisfaction by using the correlation coefficient.

Answer:

The SPSS output for correlation coefficient is given as below:

Correlations

Life Satisfaction

Hours of exercise

Pearson Correlation

Life Satisfaction

1.000

-.103

Hours of exercise

-.103

1.000

Sig. (1-tailed)

Life Satisfaction

.

.332

Hours of exercise

.332

.

N

Life Satisfaction

20

20

Hours of exercise

20

20

From above output, the correlation coefficient between the hours of exercise and life satisfaction is given as -0.103, which means there is a low or weak negative linear relationship or association exists between the given two variables such as hours of exercise and life satisfaction.

d. 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.

Answer:

The amount of variation in the life satisfaction ranking is explained by the coefficient of determination or the value of R square. Coefficient of determination is given as below:

Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.103a

.011

-.044

2.53529

a. Predictors: (Constant), Hours of exercise

The value of coefficient of determination or R square is given as 0.011, which means only 1.1% of the variation in the dependent variable life satisfaction ranking is explained by the independent variable hours of exercise.

e. Develop a model of the linear relationship using the regression line formula.

Answer:

SPSS output for the required regression model is given as below:

ANOVAb

Model

Sum of Squares

df

Mean Square

F

Sig.

1

Regression

1.252

1

1.252

.195

.664a

Residual

115.698

18

6.428

Total

116.950

19

a. Predictors: (Constant), Hours of exercise

b. Dependent Variable: Life Satisfaction

As the p-value for this regression model is 0.664, it is not statistically significant model.

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

Regression line is given as below:

Life satisfaction = 5.671 – 0.070*Hours of exercise

Descriptive Statistics

Mean

Std. Deviation

N

Life Satisfaction

5.0500

2.48098

20

Hours of exercise

8.8500

3.66024

20