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score is normally distributed. In contrast, if Asymp.Sig0.05, the hypothesis is rejected which means the score is not normal Hatch and Farhady, 1982, p.88.
In addition, if the data is not normally distributed, Mann-Whitney test will be administered to test the hypothesis and SPSS 20.0 will be calculated the result.
3.4.3.2 Homogeneity Variance
The homogeneity variance test used Levene test in SPSS program. This step did after find out that pre-test and post-test score are normally distributed. The
steps are as follows: 1.
Setting the hypothesis, H =data between the two groups are homogeny
2. Setting the level of significance α at 0.05
3. Measuring the homogeneity variance using Levene’s test
4. Comparing the result of Leven’s test and alpha level of significant If
Asymp.Sig.0.05, the null hypothesis is rejected which means the two group are not equal. In contrast, if Asymp.Sig0.05, the hypothesis is not rejected
which means variance data of two group are equal or the data are homogenous Hatch Farhady, 1982, p.88.
3.4.3.3 Independent t-Test
Analyzing the difference between means of experimental and control group, the independent t-test was used to reveal it.In this research, the independent
sample test was analyzed using computation with IBM Statistics 20.0. There are some significant criteria in analyzing independent t-test, as follow:
1. The level of significant is α = 0.05
2. Analyzing the independent t-test by using SPSS 20.0
3. Determining t-test hypothesis.
a. t
obt
t
crit
= H
o
is accepted and there is no significant difference between both of groups in pretest mean.
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b. t
obt
t
crit
= H
o
is rejected and there is significant difference between both of groups in pretest mean Hatch Farhady, 1982, p.88.
3.4.3.4 Paired-sample T-tes
Paired t-test was used to find out the differences between pre-test and post- test in each group.In this research, the independent sample was analyzed using
IBM SPSS statistics 20.0. The steps are as follows: 1.
Setting the hypothesis, H0= there is no significant difference between students’ writing score in pre-test and post-test score.
2. Setting the level of significance α at 0.05.
3. Calculating t-test score using IBM SPSS statistics 20.0
4. Comparing t-obtained and t-critical. If t-obtained t-critical, it means that the
null hypothesis is rejected, there is a significant difference between the scores before and after the treatment. In contrary, if t-obtained t- critical, the
hypothesis is not rejected; there is no significant difference between treatment score before and after the treatment, Hatch Farhady, 1982, p.88.
3.4.3.5 Effect Size
The effect size computation is conducted to check the level of effect of treatmentafter t-test calculation by using IBM SPSS Statistics 20.00 from
independent t-test of post-test. The effect size is used to determine how significance
the impact of treatment to the experimental group’s score. Effect size has positive correlation to its value, the larger impact of treatment Collidge,
2000. The formula of effect size:
� = �
2
�
2
+ ��
r : effect size t : independent t-test value
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df : degree of freedom Value of effect size is interpreted by following scale:
Table 3.5 Scale of effect size
Effect Size r value
Small .100
Medium .243
Large .371
This chapter has presented the methodology of the research including research method, population and sample, data collection, research procedures,
data analysis. Then, the findings and the discussions of the data collected will be explained in more detail in the next chapter.
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CHAPTER V CONCLUSIONS AND SUGGESTIONS
This part presentsthe research conclusions and suggestions. The conclusions are explained from the analysis of the research findings. Meanwhile, the
suggestions are expected to give a contribution for further researchers and English teachers.
5.1 Conclusions