data analysis using spss t test 1224391361027694 8
TRANSCRIPT
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Data Analysis Using
SPSSt-test
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t-test
Used to test whether there issignificant difference between themeans of two groups, e.g.:
Male v female
Full-time v part-time
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t-test
Typical hypotheses for t-test:a) There is no difference in affective
commitment (affcomm) between male
and female employeesb) There is no difference in continuance
commitment (concomm) between maleand female employees
c) There is no difference in normativecommitment (norcomm) between maleand female employees
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Performing T-test
Analyze
Compare Means
Independent-Samples T-test
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Performing T-test
Select the variables to test (TestVariables), in this case:
affcomm
concomm
norcomm
And bring the variables to the TestVariablesbox
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Performing T-test
Select the grouping variable, i.e.gender; bring it to the groupingvariablebox
Click Define Groups
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Performing T-test
Choose Use specified values
Key in the codes for the variablegender as used in the ValueLabels. In this case:
1 - Male
2 - Female
Click Continue, then OK
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T-Test: SPSS Output
Group Statistics
357 3.49720 .731988 .038741
315 3.38016 .696273 .039231
357 3.18838 .756794 .040054
315 3.15159 .666338 .037544
357 3.24090 .665938 .035245
315 3.27540 .647409 .036477
GENDER OF
RESPONDENT
MALE
FEMALE
MALE
FEMALE
MALE
FEMALE
affcomm
concomm
norcomm
N Mean Std. Deviation
Std. Error
Mean
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Independent Samples Test
1.048 .306 2.116 670 .035 .117040 .055308 .008442 .225638
2.123 666.213 .034 .117040 .055135 .008780 .225300
5.353 .021 .665 670 .506 .036788 .055335 -.071863 .145440
.670 669.997 .503 .036788 .054899 -.071006 .144582
.656 .418 -.679 670 .497 -.034500 .050813 -.134272 .065271
-.680 663.726 .497 -.034500 .050723 -.134097 .065096
Equal variances
assumedEqual variances
not assumed
Equal variances
assumed
Equal variances
not assumed
Equal variances
assumed
Equal variances
not assumed
affcomm
concomm
norcomm
F Sig.
Levene's Test for
Equality of Variances
t df Sig. (2-tailed)
Mean
Difference
Std. Error
Di ffe rence Lower Upper
95% Confidence
Interval of the
Difference
t-test for Equal ity of M eans
T-test: SPSS Output
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From the SPSS output, we areable to see that the means of therespective variables for the twogroups are:
Affective commitment (affcomm) Male 3.49720 Female 3.38016
Continuance commitment (concomm) Male 3.18838 Female 3.15159
Normative commitment (norcomm) Male 3.24090 Female 3.27540
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T-test: Interpretation
For the variable affcomm
Levenes Test for Equality of Variancesshows that F (1.048) is not significant
(0.306)* therefore the Equal variancesassumed row will be used for the t-test.
* This score (sig.) has to be 0.05 or less to beconsidered significant.
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T-test: Interpretation
Under the t-test for Equality ofMeans look at Sig. (2-tailed)for Equal variances assumed.
The score is 0.035 (which is lessthan 0.05), therefore there is asignificant difference betweenthe means of the two groups.
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Independent Samples Test
1.048 .306 2.116 670 .035 .117040 .055308 .008442 .225638
2.123 666.213 .034 .117040 .055135 .008780 .225300
5.353 .021 .665 670 .506 .036788 .055335 -.071863 .145440
.670 669.997 .503 .036788 .054899 -.071006 .144582
.656 .418 -.679 670 .497 -.034500 .050813 -.134272 .065271
-.680 663.726 .497 -.034500 .050723 -.134097 .065096
Equal variances
assumedEqual variances
not assumed
Equal variances
assumed
Equal variances
not assumed
Equal variances
assumed
Equal variances
not assumed
affcomm
concomm
norcomm
F Sig.
Levene's Test for
Equality of Variances
t df Sig. (2-tailed)
Mean
Difference
Std. Error
Di ffe rence Lower Upper
95% Confidence
Interval of the
Difference
t-test for Equal ity of M eans
T-test: Interpretation
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T-test: Interpretation
For the variable concomm
Levenes Test for Equality of Variancesshows that F (5.353) is significant
(0.021)* therefore the Equal variancesnot assumedrow will be used for the t-test.
* This score (sig.) is less than 0.05, so thereis significant different in the variances of thetwo groups.
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T-test: Interpretation
Under the t-test for Equality ofMeans look at Sig. (2-tailed) forEqual variances not assumed.
The score is 0.503 (which is morethan 0.05), therefore there is nosignificant difference between themeans of the two groups.
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Independent Samples Test
1.048 .306 2.116 670 .035 .117040 .055308 .008442 .225638
2.123 666.213 .034 .117040 .055135 .008780 .225300
5.353 .021 .665 670 .506 .036788 .055335 -.071863 .145440
.670 669.997 .503 .036788 .054899 -.071006 .144582
.656 .418 -.679 670 .497 -.034500 .050813 -.134272 .065271
-.680 663.726 .497 -.034500 .050723 -.134097 .065096
Equal variances
assumedEqual variances
not assumed
Equal variances
assumed
Equal variances
not assumed
Equal variances
assumed
Equal variances
not assumed
affcomm
concomm
norcomm
F Sig.
Levene's Test for
Equality of Variances
t df Sig. (2-tailed)
Mean
Difference
Std. Error
Di ffe rence Lower Upper
95% Confidence
Interval of the
Difference
t-test for Equal ity of M eans
T-test: Interpretation
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T-test: Interpretation
For the variable norcomm
Levenes Test for Equality of Variancesshows that F (0.656) is not significant
(0.418)* therefore the Equal variancesare assumedrow will be used for the t-test.
* This score (sig.) is more than 0.05, so thereis no significant different in the variances ofthe two groups.
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T-test: Interpretation
Under the t-test for Equality ofMeans look at Sig. (2-tailed) forEqual variances assumed.
The score is 0.497 (which is morethan 0.05), therefore there is nosignificant difference between themeans of the two groups.