CHAPTER IV: FINDING AND DISCUSSION
D. Inferential Data Analysis
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Statistic df Sig.
Pre-test Experiment Class .968 30 .496
Pre-test Control Class .979 30 .802
Post-test Experiment Class .977 30 .743
Post-test Control Class .963 30 .363
According to the normality test above, it showed that the probability value of t statistic > 0,05 level of significant. Then the data meet the assumption of normally. Thus, the independent and dependent variables have a normal distribution and can be used for the next test.
2. The Homogeneity Test
The homogeneity test aims to determine whether a variance from two or more data groups is homogeneous or not. The IBM SPSS V 25 for Windows and the Levene statistic were utilized in this homogeneity test. Here are the results of the calculation:
Table 5.2
Result of Homogeneity Test of Pre-test Test of Homogeneity of Variance
Levene Statistic df1 df2 Sig.
Result of Pre-test
Based on Mean 1.303 1 58 .258
Based on Median 1.268 1 58 .265
Based on Median and with adjusted df
1.268 1 57.680 .265
Based on trimmed mean 1.346 1 58 .251
From the table, the significance level of homogeneity in the pretest is 0.258 >
0.05, which indicated that the score of the pre-test in the experiment class and control class was homogeneous.
45 Table 5.2
Result of Homogeneity Test of Post-test Test of Homogeneity of Variance
Levene Statistic df1 df2 Sig.
Result of Post-test
Based on Mean 6.950 1 58 .011
Based on Median 5.313 1 58 .025
Based on Median and with adjusted df
5.313 1 42.469 .026
Based on trimmed mean 6.652 1 58 .012
Based on the table above, significance level of homogeneity in post-test is 0.011
< 0.05, which indicated that score of post-test in experiment class and control class was not homogeneous.
3. Paired Sample T-test of Control Class
Paired sample t-test was conducted to find out the difference in the students’
writing recount text using comic strips in experimental class and not using comic strips in control class.
The result of Paired Sample T-test of control class that calculated by IBM SPSS V 25 software for windows can be seen on the following table:
Table 6.1
Result Paired Sample Statistics Control Class Paired Samples Statistics
Mean N Std. Deviation Std. Error Mean
Pair 1 Pre-Test Control Class 64.13 30 12.202 2.228
Post-Test Control Class 75.53 30 9.999 1.826
The table of paired sample statistics shows the descriptive value of each variable in the paired samples. The mean score of the pre-test is 64.13 and the distribution of data (Std Deviation) is 12.202 with a standard error (Std. Error Mean) is 2.228.
Meanwhile, the mean score of the post-test is 75.53 and the distribution of data (Std.
Deviation) is 9.999 with a standard error (Std. Error Mean) is 1.826. Based on the
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result that was previously explained, it can be assumed that results in the post-test are higher than the pre-test result.
Table 6.2
Result of Paired Sample Test in Control Class 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
Pre-Test CC Post-Test CC
-11.400 6.616 1.208 -13.870 -8.930 -9.438 29 .000
Based on result paired sample test in control class, value of sig. (2- tailed) >
0.05. The result from Sig. (2-tailed) is 0.000 It means, H0 is rejected and Ha is accepted.
4. Paired Sample T-test of Experimental Class Table 6.3
Result Paired Sample Statistics Experimental Class Paired Samples Statistics
Mean N Std. Deviation Std. Error Mean
Pair 1 Pre-test EC 65.07 30 10.228 1.867
Post-Test EC 84.20 30 5.378 .982
The result of the paired sample statistic in the experiment class showed the descriptive value of each variable in the paired samples. The mean score of the pre- test is 65.07 and the distribution of data (Std. Deviation) is 10.228 with a standard error (Std. Error Mean) is 1.867.
Meanwhile, the mean score of the post-test is 84.20 and the distribution of the data (Std Deviation) is 5.378 with a standard error (Std Error Mean) is 982. Based
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on the result that was previously explained, it can be assumed that results in the post-test are higher than the pre-test result.
Table 6.4
Result of Paired Sample Test in Experimental Class 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 Pre-test EC
Post-Test EC
-19.133 8.513 1.554 -22.312 -15.955 -12.311 29 .000
Based on result paired sample test in control class, value of sig. (2- tailed) <
0.05. The result from Sig. (2-tailed) is 0.000 < 0.05. It means, Ha is accepted and H0 is rejected.
5. Independent Sample T-test of Pre-test
Independent sample T-test used to determine the differences mean of two populations/groups independent data. The result of group pre-test statistic calculated by IBM SPSS V25 software for windows are presented in this table below:
Table 7.1
Result of Group Statistics of Pre-test Group Statistics
Class N Mean Std. Deviation Std. Error Mean
Result of Pre-test Experiment Class 30 65.07 10.228 1.867
Control Class 30 64.13 12.202 2.228
The group statistics of pre-test describes the descriptive analysis of the processed data. The mean table showed the average value of each variable. According to table above, it can be seen that the mean of pre-test in control class is 64.13 and mean score in experiment class is 65.07. The mean difference between this both classes
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have a little different, it can be inferred that the students’ writing of recount text are relative the same. The standard deviation was used to measure the level of risk, which in in the pre-test of control class is 12.202 and the standard deviation in the experiment class is 10.228. Standard error mean is used to determine how well the average data from the sample data for each variable can estimate the population means. In the control class, the standard error mean is 2.228 and in the experimental class is 1.867. So, it can be said that the data variants between the control class and the experiment class were homogeneous.
Table 7.2
Result of Independent Sample Test of Pre-test
In Levene’s test for quality of column variances have significance value of 0.258
> 0.05. It showed that the two variance were homogeneous, then the use of variance to compare the population mean (t-test for Equality of Means) in t-test must be based on equal variance assumed. In addition, based on table above, the equal variances assumed that known the sig value is 0.749 > 0.05, as the basis for decision making in the independent t-test, it can be concluded that H0 is accepted and Ha is rejected. Therefore, it can be said that there was no difference between the average students’ learning outcomes in pre-test in the control and the experiment class.
6. Independent Sample T-test of Post-test
Independent Samples Test
Levene's Test for Equality of
Variances t-test for Equality of Means
F Sig. t df
Sig. (2- tailed)
Mean Differen ce
Std. Error Difference
95% Confidence Interval of the
Difference Lower Upper Result
of Pre- test
Equal variances assumed
1.303 .258 .321 58 .749 .933 2.907 -4.885 6.752
Equal variances not assumed
.321 56.284 .749 .933 2.907 -4.889 6.756
49 Table 7.3
Result of Group Statistics of Post-test Group Statistics
Class N Mean Std. Deviation Std. Error Mean
Result of Post-test Experiment Class 30 84.20 5.378 .982
Control Class 30 75.53 9.999 1.826
Based on the group statistics of post-test table above, the mean table showed the average value of each variable. It can be seen from the table above that the mean of post-test in control class is 75.53 and the mean in experimental class is 84.20.
Therefore, this means that learning outcomes in learning writing using comic strips in the experiment class are higher than in the control class. N indicates the amount of data as many 30 in both-class. Standard deviation used to measure level of the risk, in the post-test of control class is 9.999 and the post-test in experimental class is 5.378. Standard error mean was used to determine how well the average data from the sample data of each variable can estimate the population means. Standard error mean in the control class is 1.826 and in the experiment class is 982. The average score (mean) of post-test, it can be said that the data of post-test is higher dan pre-test.
Table 7.4
Result of Independent Sample of Post-test Independent Samples Test
Levene's Test for Equality of
Variances t-test for Equality of Means
F Sig. t df
Sig. (2- tailed)
Mean Differen ce
Std.
Error Differen
ce
95% Confidence Interval of the
Difference Lower Upper Result of
Post-test
Equal variances assumed
6.950 .011 4.181 58 .000 8.667 2.073 4.517 12.816
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Equal variances not assumed
4.181 44.483 .000 8.667 2.073 4.490 12.843
In Levene’s test for quality of column variances have significance value of 0.011
< 0.05. It showed that the two variance were not homogeneous, then the use of variance to compare the population mean (t-test for Equality of Means) in t-test must be based on equal variance not assumed. In relation on the table above, the equal variances not assumed that known the sig 2-tailed value is 0.000 < 0.05, as the basis for decision making in the independent t-test, it can be concluded that H0
is rejected and Ha is accepted. Therefore, it can be said that there was difference between the average students’ learning outcomes in post-test in the control class and the experiment class.