SPSS Assignment: Data Analysis using Paired and Independent t-tests

This SPSS assignment analyzes data using paired and independent samples t-tests. The assignment begins with an analysis using a paired samples t-test to compare satisfaction levels with current weight and weight at age 18, concluding that satisfaction with current weight is significantly less. The second part employs an independent samples t-test to compare the total score of positive psychological attitudes (IPPA) between married and unmarried individuals, revealing that married individuals have a significantly higher total IPPA score. The document provides detailed statistical outputs, including means, standard deviations, t-statistics, p-values, and confidence intervals, along with the interpretation of results and conclusions based on the analyses.

Running head: SPSS ASSIGNMENT
SPSS Assignment
Name of the Student:
Name of the University:
Author’s Note:

1SPSS ASSIGNMENT
Table of Contents
Data analysis:..........................................................................................................................................................................2
Answer 1.............................................................................................................................................................................2
Paired sample t-test:........................................................................................................................................................2
Answer 2.............................................................................................................................................................................3
Comparison of Means:....................................................................................................................................................3
Independent sample t-test:..............................................................................................................................................3
References:.............................................................................................................................................................................5

2SPSS ASSIGNMENT
Data analysis:
The data analysis takes into account mainly four variables. The scaled ordinal variables are utilised for analysis. These
are-
1. Satisfaction with current weight recorded
2. Satisfaction with weight at age 18 recorded
3. Total score of positive psychological attitudes
4. Marital status.
Answer 1.
Paired sample t-test:
Paired Samples Statistics
Mean N Std.
Deviation
Std. Error
Mean
Pair 1
satisfaction with current
weight recoded .5337 697 .49922 .01891
satisfaction with weight
at age 18 recoded .6901 697 .46278 .01753
Paired Samples Correlations
N Correlatio
n
Sig.
Pair 1
satisfaction with current
weight recoded &
satisfaction with weight
at age 18 recoded
697 .418 .000
Paired Samples Test
Paired Differences t df Sig. (2-
tailed)Mean Std.
Deviation
Std. Error
Mean
95% Confidence Interval
of the Difference
Lower Upper
Pair
1
satisfaction with
current weight
recoded -
satisfaction with
weight at age 18
recoded
-.15638 .51966 .01968 -.19503 -.11774 -7.945 696 .000
(Kim, 2015)
Hypotheses:
Null Hypotheses (H0): Average satisfaction with current weight recorded is equal to the average satisfaction with weight
at age 18 recorded.
Alternative Hypothesis (HA): Average satisfaction with current weight recorded is less than the average satisfaction with
weight at age 18 recorded.
Test applied:
Paired sample t-test is applied to test the equality of average scores of these two variables.
Level of significance:
The preassigned level of significance is assumed as 0.05.
Calculated test statistic:
The calculated t-statistic = -7.945 with 696 degrees of freedom.

3SPSS ASSIGNMENT
Calculated p-value:
The calculated p-value for t (-7.945, 696) = 0.0.
Inference:
As, 0.05>0.0, therefore, t critical > t sig. It could be interpreted that the null hypothesis could be rejected at 5% level of
significance. The alternative hypothesis is accepted here. Hence, it is 95% probable that average satisfaction with current
weight recorded is less than the average satisfaction with weight at age 18 recorded (Pohlert, 2014).
Conclusion:
It could be concluded that average satisfaction level with current weight recorded is less than the average satisfaction
with weight at age a8 recorded.
Therefore, being satisfied with current weight differ significantly from satisfaction with weight at age 18.
Answer 2.
Step 1.
Comparison of Means:
Case Processing Summary
Cases
Included Excluded Total
N Percent N Percent N Percent
total*ms_new 543 77.5% 158 22.5% 701 100.0%
Report
total
ms_new Mean N Std. Deviation Std. Error of Mean
Never married 150.5297 219 25.52608 1.72489
Married 157.1481 324 26.44141 1.46897
Total 154.4788 543 26.25427 1.12668
Step 2.
Independent sample t-test:
Group Statistics
Marital
Status
N Mean Std.
Deviation
Std. Error
Mean
total
Never
married 219 150.5297 25.52608 1.72489
Married 324 157.1481 26.44141 1.46897
Independent Samples Test
Levene's
Test for
Equality of
Variances
t-test for Equality of Means
F Sig. t df Sig. (2-
tailed)
Mean
Difference
Std. Error
Difference
95% Confidence
Interval of the
Difference
Lower Upper

4SPSS ASSIGNMENT
total
Equal
variances
assumed
.211 .646 -2.901 541 .004 -6.61847 2.28115 -11.09946 -2.13747
Equal
variances
not
assumed
-2.921 478.878 .004 -6.61847 2.26564 -11.07029 -2.16665
(Cronk, 2017)
Step 1.
Out of 543 samples, 219 samples have never married and 324 samples have married. The means of total score of positive
psychological attitudes of married and never married persons are 157.1481 and 150.5297. The standard deviation of total
score of positive psychological attitudes of married and unmarried persons are 26.4414 and 25.52608. The standard error
mean of total score of positive psychological attitudes of married and unmarried persons are 1.469 and 1.725.
The total IPPA score delivers different means, standard deviation and standard error mean respectively according to the
group wise marital status.
Step 2.
Hypotheses:
Null Hypotheses (H0): Average positive psychological attitudes total score (total IPPA score) for married persons is equal
to the average positive psychological attitudes total score (total IPPA score) for unmarried persons.
Alternative Hypothesis (HA): Average positive psychological attitudes total score (total IPPA score) for married persons
is greater than the average positive psychological attitudes total score (total IPPA score) for unmarried persons.
Test applied:
Independent sample t-test is applied to test the equality of average total scores of these two variables.
Level of significance:
The preassigned level of significance is assumed as 0.05.
Calculated test statistic:
The calculated t-statistic = -2.901 with 541 degrees of freedom when assumption of equal variances is considered.
The calculated t-statistic = -2.921 with 479 degrees of freedom when assumption of unequal variances is considered.
Calculated p-value:
The calculated p-value for t (-2.901, 541) = 0.004 and t (-2.921, 479) = 0.004.
Inference:
As, 0.05>0.004, therefore, t critical > t sig. It could be interpreted that the null hypothesis could be rejected at 5% level of
significance. The alternative hypothesis is accepted here. Hence, it is 95% probable that average positive psychological
attitudes total score (total IPPA score) for married persons is greater than the average positive psychological attitudes
total score (total IPPA score) for unmarried persons.
Conclusion:
It could be concluded that average positive psychological attitudes total score (total IPPA score) for married persons is
greater than the average positive psychological attitudes total score (total IPPA score) for unmarried persons.
Therefore, being positive psychological attitudes total score (total IPPA score) of married persons differ significantly
from positive psychological attitudes total score (total IPPA score) of unmarried persons.

5SPSS ASSIGNMENT
References:
Cronk, B. C. (2017). How to use SPSS®: A step-by-step guide to analysis and interpretation. Routledge.
Kim, T. K. (2015). T test as a parametric statistic. Korean journal of anesthesiology, 68(6), 540-546.
Pohlert, T. (2014). The pairwise multiple comparison of mean ranks package (PMCMR). R package, 2004-2006.