Statistical Analysis Using SPSS

STATISTICAL ANALYSIS USING SPSS1
STATISTICAL ANALYSIS USING SPSS
Name of the Student:
Name of the University:
Author Note:

STATISTICAL ANALYSIS USING SPSS2
Answer 1
Here the data consists of hours of exercise per week and life satisfaction (rank in 1-10
scale) of 20 individuals. The main objective is to find a relationship between the workout hours
and happiness.
a. From the table1, it can be seen that the mean hours of physical activity per week is
8.85. This means that on average, an individual workout for 8.85 hours per week.
Table 1:
Descriptive Statistics
N Mean Std. Deviation Variance
Hours_of_Exercise 20 8.85 3.660 13.397
Valid N (listwise) 20
b. Table 1 shows that the variance and standard deviations of exercise hours are 13.40
and 3.66 respectively. Hence the variance shows that the practice hours of the
individuals do not have a wide range of variation. Moreover, standard deviation
implies that in most of the cases, the gym times are nearby the mean time.
c. Table 2 shows the linear association between the two variables- exercise duration and
happiness. Exercise duration and pleasures in life are negatively correlated, r= -0.103,
p=0.664.

STATISTICAL ANALYSIS USING SPSS3
Table 2:
Correlations
Hours_of_Exercise Life_Satisfaction
Hours_of_Exercis
e
Pearson
Correlation
1 -.103
Sig. (2-tailed) .664
N 20 20
Life_Satisfaction Pearson
Correlation
-.103 1
Sig. (2-tailed) .664
N 20 20
d. Table 3 shows that the R square value for the linear regression model is 0.011. Hence,
it can be concluded that 1.1% variation in life satisfaction can be explained by the
workout hours per week of an individual.
Table 3:
Model Summaryb
Model R
R
Square
Adjusted R
Square
Std. Error of the
Estimate
Change Statistics
Durbin-
Watson
R Square
Change
F
Change df1 df2
Sig. F
Change
1 .103a .011 -.044 2.535 .011 .195 1 18 .664 2.052
a. Predictors: (Constant), Hours_of_Exercise
b. Dependent Variable: Life_Satisfaction
e. The linear regression formula taking exercise time as independent and life satisfaction
as dependent variable can be written as (Table 4),
Life Satisfaction=5.671−0.07 Hours of Exercise

STATISTICAL ANALYSIS USING SPSS4
that means change in the duration of physical activity time has inverse impact on a
person’s life enjoyment.
Table 4:
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