SPSS report on conducting independent t test & One way ANOVA test

1. SUBMITTED BY: GROUP 3
VISHALI AGGGARWAL – 20DM238
VISHAL DIGAMBAR SHINDE – 20DM246
VRINDA MAHESHWARI- 20DM248
HARJAS PREET SINGH-20DM266
SHIVAM TANEJA- 20DM285
AYUSHMAN SINGH RATNU – 20DM292
Research Methodology Project Report
SEC - D

2. Letter of Transmittal
TO,
Professor Amaranth Bose
Chairperson - Internal Quality Assurance Cell
Professor of Operations and Decision Science
BIMTECH
Dear Sir,
We are submitting herewith our report entitled “Research
Methodology Project” as a partial fulfillment of Research
Methodology Course requirement.
The purpose of this report is to conduct respective statistic test
on Data-set-39 “Survey” using service code given to us and
come to conclusion regarding relationship between self-esteem,
education and age. The proposal shows a detail analysis of
relationship between person education level with self-esteem.
We hope that this report will merit your approval.
Regards,
Team 3
Section –D
Trimester 2
PGDM - BIMTECH

3. TABLE OF CONTENT:
S.no Content
1 Executive Summary
2 List of Tables
3 Sample Description( Set-39):
i. Sex
ii. Self Esteem
iii. Age
iv. Educational Background
4 Research Question 1:
i. Hypothesis Formation
ii. Test Statistics
iii. Output
iv. Conclusion
5 Research Question 2
i. Hypothesis Formation
ii. Test Statistics
iii. Output
iv. Conclusion
6 Limitations
7 Conclusion
8 Appendix

4. Executive Summary
The data file used for the study was Set-39 “survey” provided to
us. The data was designed in such a way that it study could
conclude the relationship of various materialistic parameter like
education and age with a person psychological parameters like
Self-esteem. We were provided with two research questions
related to person’s self-esteem relation to various parameters.
Q1) Does education attainment improve self-esteem?
One way ANOVA test was used to derive the conclusion. The ANOVA
test will tell you whether there is a significant difference between the
means of two or more levels of a variable. The significant value(i.e. p
value) after performing test was found to be 0.077 which is greater than
the α level of 0.05 therefore we failed to reject null hypothesis( H0 ).
There was no statistically significant difference between two variables
Q2) Does self-esteem vary significantly between
younger and older age groups?
Independent sample T test was run to determine if there was a
significant difference between the self-esteem of young people
and old people. The significance of the mean difference between
two age group was found to be 0.010 which is less than the α
level of significance, and t value as -2.601 we will reject the null
hypothesis and conclude that old has more self-esteem than
young age.

5. List of Table:
Table no. Content
1 Frequency table for sample size and sex
2 Descriptive statistic for sample size and sex
3 Descriptive Statistics for Self esteem
4 Frequency table for self esteem
5 Descriptive statistics for age group
6 Frequency table for age group
7 Descriptive statistics for Education
8 Frequency table for education
9 Descriptive statistics for self-esteem in comparison
with education
10 ANOVA table for research question 1
11 Tukey HSD table for research question 1
12 Group statistics table for Self-esteem in
comparison with age group
13 Independent sample T test table for research
question 2

6. Sample description
Our sample consists the population of 350. The respondents were also asked information about
their previous educational career (type of secondary school attended, mark at exit) and current
academic career, Age, gender, marital stats, no. of children, smoking habit etc. The
questionnaire contained two question intended to measure self-esteem with respect to
educational background and age groups.
 SEX:
The sample consists of 148 males and 202 females with mean of 1.58 and standard deviation of 0.495 in
the sex index.
Table 1 and Table 2
 Self- Esteem:
Social psychological scales, such as self-esteem, play an important role in research on educational
attainment. In social psychology, self-esteem is a term which refers to an individual’s perception of his
or her own worth. Further, self- esteem is conceptualized as an enduring personality characteristic.
Generally it has been argued that a positive relationship exists between self-esteem and academic
performance.
Self-esteem is mentioned as sest1 to sest10 with a range of 10-40 in SPSS data file. This data
was recoded into tslfest2 (4 groups for evaluation purpose). The groups are “strongly
disagree”(10-16), “disagree”(17-24), “agree”(25-32), strongly agree(33-40) .
Sex
Frequency Percent Valid
Percen
t
Cumulati
ve
Percent
Vali
d
1 148 42.3 42.3 42.3
2 202 57.7 57.7 100.0
Total 350 100.0 100.0
Statistics
sex
N Valid 350
Missing 0
Mean 1.58
Std. Deviation .495
Percentiles 25 1.00
50 2.00
75 2.00

7. Statistics
tslfest2(recoded variable)
N Valid 348
Missing 2
Mean 3.5805
Std. Deviation .64586
Percentiles 25 3.0000
50 4.0000
75 4.0000
Table 3
tslfest2
Frequency Percent Valid Percent Cumulative
Percent
Valid Disagree 30 8.6 8.6 8.6
Agree 86 24.6 24.7 33.3
Strongly agree 232 66.3 66.7 100.0
Total 348 99.4 100.0
Missing System 2 .6
Total 350 100.0
Table 4
 Age
Table 5
Statistics
tslfest (original variable)
N Valid 348
Missing 2
Mean 33.66
Std. Deviation 5.339
Percentiles 25 30.00
50 35.00
75 38.00
Statistics age2(new variable)
N Valid 350
Missing 0
Mean 2.0171
Std. Deviation .82562
Percentile
s
25 1.0000
50 2.0000
75 3.0000
Statistics age(original variables)
N Valid 350
Missing 0
Mean 38.25
Std. Deviation 13.602
Percentiles 25 26.00
50 36.00
75 48.00

8. Age of every individual is mentioned in the data give as “age”. We recorded the data and
arranged into a new variable “age2” (into three groups) with range like “young” (18-29yr),
“middle aged”(30-44), “old age”(45-90). This grouped data has a mean of 2.0171 and a
standard deviation of 0.82562 .
Table 6
 Educational background
The data set consist of highest level of educational of the population. Each of the educational level
was given in form of numerical ranged from 1 to 6. The educational levels were given some names
for better understanding like Primary(1), Some secondary(2), Completed high school(3), Some
additional training(4), Completed undergraduate(5), Completed postgraduate(6). It has a mean of
4.07 and standard deviation of 1.239 .
Statistics
educ
N Valid 350
Missing 0
Mean 4.07
Std. Deviation 1.239
Percentile
s
25 3.00
50 4.00
75 5.00
Table 7
age2
Frequency Percent Valid Percent Cumulative
Percent
Valid Young 116 33.1 33.1 33.1
middle age 112 32.0 32.0 65.1
old age 122 34.9 34.9 100.0
Total 350 100.0 100.0

9. Table 8
Educt
Frequency Percent Valid Percent Cumulative
Percent
Valid Primary 2 .6 .6 .6
Some secondary 43 12.3 12.3 12.9
Completed High school 68 19.4 19.4 32.3
Some additional training 98 28.0 28.0 60.3
completed undergraduate 92 26.3 26.3 86.6
Completed Postgraduate 47 13.4 13.4 100.0
Total 350 100.0 100.0

10. 1): Does educational attainment improve
self-esteem?
Hypothesis:
Null hypothesis H0: µ1 = µ2= µ3= µ4= µ5=µ6
Alternate hypothesis Ha: Not all the means are equal
Where, µ1 = Mean number of students in primary.
µ2 = Mean number of students who are in secondary.
µ3 = Mean number of students who completed high school.
µ4 = Mean number of students who are in additional training
µ5 = Mean number of students who completed undergraduate.
µ6 = Mean number of students who completed postgraduate
we will take Level of Significance i.e. α = 0.05
Test statistic :
We will be using ANOVA for the research to know how the educational attainment
improves self-esteem. The one-way analysis of variance (ANOVA) is used to determine
whether there are any statistically significant differences between the means of two or
more independent (unrelated) groups (although you tend to only see it used when there
are a minimum of three, rather than two groups).ANOVA Test Procedure in SPSS
Statistics :
The six steps below show you how to analyze your data using a one-way ANOVA in SPSS
Statistics .
1. Click Analyze > Compare Means > One-Way ANOVA...
2. Select One-Way ANOVA dialogue box
3. Transfer the dependent variable, SELF ESTEEM, into the dependent list box and
the independent variable, EDUCATION, into the factor box using the
appropriate buttons

11. 4. Click on the button. Tick the Turkey checkbox and continue
5. Click on the button. Tick the Descriptive checkbox in the statistic area,
and means plot if necessary.
6. Click continue and then ok button
Output:
The descriptive table provides some very useful descriptive statistics, including the
mean, standard deviation and 95% confidence intervals for the dependent variable (
self-esteem i.e. tslfest2) for each separate group( primary, some secondary, completed
high school etc.), as well as when all groups are combined (Total).
Table 9
ANOVA table shows the output of the analysis and whether there is a statistically
significant difference between our group means. We can see that the significance value
is 0.077 (i.e., p = .077), which is greater than 0.05 (i.e. level of significance) . And,
therefore, there is a statistically significant difference in the mean length of self-esteem
between the different educational groups taken.
Descriptive table
Table 9
tslfest2 N Mean Std.
Deviation
Std.
Error
95% Confidence
Interval for Mean
Minimum Maximum
Lower
Bound
Upper
Bound
Primary 2 4.0000 .00000 .00000 4.0000 4.0000 4.00 4.00
Some secondary 42 3.5476 .67000 .10338 3.3388 3.7564 2.00 4.00
Completed High
school
68 3.4118 .75775 .09189 3.2283 3.5952 2.00 4.00
Some additional
training
97 3.5567 .64500 .06549 3.4267 3.6867 2.00 4.00
completed
undergraduate
92 3.6522 .60100 .06266 3.5277 3.7766 2.00 4.00
Completed
Postgraduate
47 3.7447 .48759 .07112 3.6015 3.8878 2.00 4.00
Total 348 3.5805 .64586 .03462 3.5124 3.6486 2.00 4.00

12. Table 10
For multiple comparison, we use Turkey HSD where we can find the significance value
among the different educational groups
tslfest2
Tukey HSD
a,b
Educ N Subset for alpha = 0.05
1
Completed High school 68 3.4118
Some secondary 42 3.5476
Some additional traning 97 3.5567
completed undergraduate 92 3.6522
Completed Postgraduate 47 3.7447
Primary 2 4.0000
Sig. .298
Means for groups in homogeneous subsets are displayed. Table 11
a. Uses Harmonic Mean Sample Size = 10.328.
b. The group sizes are unequal. The harmonic mean of the group sizes is used. Type I error levels are not
guaranteed.
Table 11
Observations:
 The significance value observed ( p-value) is 0.077 for F = 2.008
Decision and conclusion:
The p- value is more than 0.05, hence we do not reject Ho ,We cannot conclude that the
educational attainment does improve the self-esteem.
ANOVA
tslfest2
Sum of
Squares
df Mean Square F Sig.
Between Groups 4.128 5 .826 2.008 .077
Within Groups 140.619 342 .411
Total 144.747 347

13. 2: Does self-esteem vary significantly
between younger and older age groups?
Hypothesis:
H0: µ1 - µ2 = Do,
Ha: µ1 - µ2 ≠ Do,
Where µ1 is the mean of younger age group ( age- 18 to 29) and µ2 is the mean of older
age group (age- 45 to 90 years).
Specify the level of significance. α = 0.05
Test statistic:
To know the self-esteem significance between young and older age groups we prefer to
perform independence sample t- test. The independent-samples t-test (or independent
t-test, for short) compares the means between two unrelated groups on the same
continuous, dependent variable.
Independence sample T-Test Procedure in SPSS Statistics :
1. Click Analyze > Compare Means > Independent-Samples T Test. Independent-
Samples T Test.
2. Transfer the dependent variable, self-esteem, into test variable box, and transfer
the independent variable, age, into the grouping variable box, by highlighting
the relevant variables and pressing the inwards arrow buttons.
3. Define the groups (treatments). Click on the button. You will be
presented with the Define Groups dialogue box where we should assign values
like 1 for young and 3 for older age group (recoded values). And then press
continues.
4. If you need to change the confidence level limits or changes how to exclude
cases, click the button. And make required changes ( in our case it is
at 95% confidence interval).

14. 5. Click the button. You will be returned to the Independent-Samples T
Test dialogue box and then press OK.
Output:
Group Statistics Table: This table provides useful descriptive statistics for the
two groups that you compared, including the mean and standard deviation
Table 12
Independent Samples Test Table: This table provides the actual results
from the independent t-test
Table 13
Group Statistics
age2 N Mean Std. Deviation Std. Error Mean
tslfest2 young 116 3.4741 .71580 .06646
old age 120 3.6917 .56205 .05131
Levene's Test for
Equality of
Variances
t-test for Equality of Means
F Sig. t df Sig. (2-
tailed)
Mean
Difference
Std.
Error
Differen
ce
95% Confidence
Interval of the
Difference
Lower Upper
tslfest2 Equal
variances
assumed
17.574 .000 -2.601 234 .010 -.21753 .08362 -.38228 -.05278
Equal
variances
not
assumed
-2.591 218.
070
.010 -.21753 .08396 -.38301 -.05205

15. Observations:
The p-value of Levene's test is printed as ".000" (but should be read as p < 0.001 --
i.e., p very small), so we reject the null of Levene's test and conclude that the
variance of young is significantly different than that of old age. This tells us that
we should look at the "Equal variances not assumed" row for the t test (and
corresponding confidence interval) results. (If this test result had not been
significant -- that is, if we had observed p > α -- then we would have used the
"Equal variances assumed" output.
Since p value(0.01) from t-test for Equality of Means table is less than 0.05 we
will reject the null hypotheses and conclude mean score for young is significantly
different from that of old age
Significant Difference test indicated that the mean score for young age group
(M=3.4741, SD=0.7158) was significantly different from older age group(M=3.6917,
SD=0.5620)
Conclusion:
Since p value (0.01) is less than level of significance i.e. 0.05 we will reject the null
hypothesis. So we can conclude that Self Esteem does not vary significantly
between young and old age groups.

16. Limitations
The ANOVA test assumes that the samples used in the analysis are "Simple
random samples." This means that a sample of individuals (data points) is taken
from a larger population (a larger data pool). The samples must also be
independent -- that is, they do not affect each other. ANOVA is generally suitable
for comparing means in controlled studies, but when the samples are not
independent a repeated measures test must be used.
Conclusion
In the research we have considered the psychological aspect like self-esteem as a
potential determinant of educational level attainment and its significance in
various age groups.
Although we could not lead to the conclusion of level of self-esteem with respect
to educational attainment, But we came to the conclusion that self-esteem varies
between different age groups and surprisingly we found that self-esteem in old
age was found to be more than that of young.

17. APPENDIX