PRETEST Based on Mean Based on Median
Based on Median And with adjusted df
Based on trimmed mean .016
.011 .011
.017 1
1 1
1 48
48 47.701
48 .900
.918
In the table, the asymp.sig is higher than the determined levelof signficance 0.05, which also can be stated that 0.9000.05. It indicates that
the null hypothesis is not rejected but the alternative hypothesis is rejected. It draws a conclusion that the variance of data is homogenous. It also implies
that the analysis of t-test can be conducted since the data is normally distributed and the variances are homogenous.
Table 3.4 Homogeneity test of post-test
Levene Statistic df1
df2 Sig.
POSTEST Based on Mean Based on Median
Based on Median and with adjusted df
Based on Trimmed Mean .108
.115 .115
.101 1
1 1
1 48
48 47.9923
48 .743
.736 .736
.751
The level of significance of this test was established at 0.05. Moreover, table 4.6 above shows that the asymp.sig is 0.743 that is greater than 0.05
0.7430.05. it indicates that the null hypothesis is not rejected and alternative hypothesis is rejected. It means that there is no difference of
variance scores between the controlled and the experimental group.
c. Independent t-test
After revealing the result of normality and homogeneity tests, the next statistical computation was analyzing independent t-test. These are the
procedures to follow in calculating the independent t-test of pretest and post-
test data:
1 Setting the level of significance p at 0.05 and establishing the alternative
hypothesis for the pretest and post-test data analysis. The hypothesis are stated as below:
H : there is no significant difference between the means in experimental
and controlled groups. H
1
: there is significant difference between the means in experimental and controlled groups.
2 Analyzing the independent t-test by using SPSS 20.0
Comparing the asymp.sig with the level of significance to test the hypothesis. If the asymp.sig 0.05 and df = 48, null hypothesis is rejected
and alternative hypothesis is not rejected. It clarifies that there is difference of means between experimental and controlled group. However, if the
asymp.sig 0.05, the null hypothesis is not rejected and alternative hypothesis is rejected. It declares that there is no difference of means
between experimental and control group.
4. Effect Size
The effect size computation is conducted to check the level of effect of treatment after the t-test calculation by using SPSS 20.0 from independent t-
test of post-test. It was used to determine the significance impact of the
treatment of the experimental group. The formula is:
√
The t refers to the t valueobtained from the independent t-test calculation on post-test data. Afterward, the df is the amount of samples minus by 2 df-
N-2. After obtaining the r value, in addition, it is analyzed by using effect size scale
2
.
Table 3.5 The Scale of Effect Size
Effect size r value
Small 0.100
Medium 0.243
Large 0.371
H. Statistical Hypothesis
According to Hatch and Farhady, hypothesis means a tentative statement about the outcomes of the research, it indicates that question must answered
by doing experiment
3
. Two hypothesis are formulated as follows:
H : µ
1
= µ
2
, or H
A
: µ
1
≠ µ
2
Specifically, the hypothesis in this study is the form of the null hypothesis and alternative hypothesis. The null hypothesis H
indicates there is no significant difference in means between controlled and experimental group.
Meanwhile, the alternative hypothesis H
A
means that there us a significant difference between controlled and experimental group.
2
Ibid., p. 106
3
Hatch and Farhady, Research Design and Statistic for applied linguistics,Los Angeles: Newbury House Publishers, Inc, 1982 p. 86.
