It can be seen as table 4.4 above, the significance of pre-test score in controlled class based on Kolmogorov-Smirnov was 0.200. If the significance score is
higher than α = 0.05, it means that the data was normal distributed. It can be concluded that the significance score of Pre-test in controlled class is normally
distributed because 0.200 is higher than 0.05 0.200 0.05. b.
Normality of Post-test
1.
Normality of Post-test in Experimental Class Table 4.5
Normality Post-test Result in Experimental Class
Tests of Normality
Kolmogorov-Smirnov
a
Shapiro-Wilk Statistic
df Sig.
Statistic df
Sig. Post_Test_Eksperiment
.132 30
.196 .919
30 .025
a. Lilliefors Significance Correction
From the table 4.5 above, it can be seen that the significance of post-test score in experimental class based on Kolmogorov-Smirnov was 0.196. If the significance
score is highe r than α = 0.05, it means that the data was normal distributed. It can be
concluded that the significance score of post-test in experimental class is normally distributed because 0.196 is higher than 0.05 0.196 0.05
2. Normality of Post-test in Controlled Class
Table 4.6 Normality Post-test Result in Controlled Class
Tests of Normality
Kolmogorov-Smirnov
a
Shapiro-Wilk Statistic
df Sig.
Statistic df
Sig. Post_Test_Controlled
.119 30
.200 .968
30 .480
. This is a lower bound of the true significance. a. Lilliefors Significance Correction
From the table 4.6 above, it can be seen that the significance of post-test score in controlled class based on Kolmogorov-Smirnov was 0.200. If the significance score
is higher than α = 0.05, it means that the data was normal distributed. It can be concluded that the significance score of post-test in controlled class is normally
distributed because 0.200 is higher than 0.05 0.200 0.05.
2. Homogeneity of Data
After the writer calculated the data by using normality test, the writer got the result that all data in pre-test and post-test of both experiment class and controlled class
have normally distributed. The next step of the calculation was finding the homogeneity of the data to see the data or sample in both classes were homogenous
or heterogeneous. If the significance of the data is higher than 0.05, it means that the data is homogenous. The result of the homogeneity test of experiment and controlled
class presented as follows: a.
Homogeneity of Pre-test
The analysis of homogeneity variances of both classes in pre-test was done by using
Levene’s statistic test in SPSS v. 22 for window. Here are the result of calculation:
Table 4.7 Homogeneity Pre-test between Experiment Class and Controlled Class
Test of Homogeneity of Variances
Pre_test_exp Levene Statistic
df1 df2
Sig. 1.650
6 20
.185
Table 4.7 showed that the significance of pre-test between experiment class and controlled class was 0.185. It can be concluded that the pre-test data of both classes
were homogeneous because the result of significance pre-test 0.185 was higher than 0.05. 0.185 0.05
b. Homogeneity of Post-test
The analysis of homogeneity variances of both classes in post-test was done by using
Levene’s statistic test in SPSS v. 22 for window. Here are the results of calculation:
Table 4.8 Homogeneity Post-test between Experiment Class and Controlled Class
Test of Homogeneity of Variances
Post_Test_Controlled Levene Statistic
df1 df2
Sig. .863
5 24
.520
Table 4.8 showed that the significance of post-test between experiment class and controlled class was 0.520. It can be concluded that the post-test data of both classes
were homogeneous because the result of significance post-test 0.520 was higher than 0.05.
After both data was proved normally distributed and homogenous, the last calculation is testing the hypothesis. The data is calculated by using t-test formula to know the
answer of the question whether there is a significance different between students’
vocabulary mastery by using suggestopedia method in experimental class and students’ vocabulary mastery without using suggesstopedia method in controlled
class. The two classes were compared, the experiment class was X variable and the controlled class was Y variable.
3.
Hypothesis Testing Tabel 4.9
The Statistical Calculation of Gain Score of Experiment Class and Controlled Class
No Students
X Students
Y X-MX
Y-MY X-MX
2
Y-MY
2
1 16
12 -4.13
0.4 17.0569
0.16 2
20 12
-0.13 0.4
0.0169 0.16
No Students
X Students
Y X-MX
Y-MY X-MX
2
Y-MY
2
3 16
8 -4.13
-3.6 17.0569
12.96 4
20 8
-0.13 -3.6
0.0169 12.96
5 16
8 -4.13
-3.6 17.0569
12.96 6
32 28
11.87 16.4
140.8969 268.96
7 8
20 -12.13
8.4 147.1369
70.56 8
36 8
15.87 -3.6
251.8569 12.96
9 36
16 15.87
4.4 251.8569
19.36 10
16 12
-4.13 0.4
17.0569 0.16
11 20
8 -0.13
-3.6 0.0169
12.96 12
12 8
-8.13 -3.6
66.0969 12.96
13 16
12 -4.13
0.4 17.0569
0.16 14
16 12
-4.13 0.4
17.0569 0.16
15 12
16 -8.13
4.4 66.0969
19.36 16
24 4
3.87 -7.6
14.9769 57.76
17 28
12 7.87
0.4 61.9369
0.16 18
28 8
7.87 -3.6
61.9369 12.96
19 24
3.87 -11.6
14.9769 134.56
20 24
16 3.87
4.4 14.9769
19.36 21
16 8
-4.13 -3.6
17.0569 12.96
22 16
16 -4.13
4.4 17.0569
19.36 23
12 8
-8.13 -3.6
66.0969 12.96
24 8
16 -12.13
4.4 147.1369
19.36 25
16 8
-4.13 -3.6
17.0569 12.96
26 36
16 15.87
4.4 251.8569
19.36 27
8 8
-12.13 -3.6
147.1369 12.96
28 28
16 7.87
4.4 61.9369
19.36 29
24 16
3.87 4.4
14.9769 19.36
30 20
8 -0.13
-3.6 0.0169
12.96
Σ
604 348
1935.467 843.2
Mean 20.133333 11.6
64.51556667 28.1066667
