2. Homogeneity of the Data
a. Pre-test Homogeneity Test Based on the calculation of normality, the writer got the result that all
data in pre-test and post-test of both experiment class and control class have been normally distributed. The next step of the calculation was finding the
homogeneity of the data. The purpose of this calculation was to see whether the data in both classes were homogenous or heterogeneous. The writer used
SPSS v.22 to find the homogeneity of the data by looking at the significant of the data. If it is higher than 0.05 it means that the data is homogeneous.
Table 4.15 Homogeneity of Pre-test Results between Experimental and Control Class
Levene Statistic df1
df2 Sig.
,085 1
84 ,772
Table 4.15 showed that the significance of pre-test score between experimental class and control class 0.772. Therefore, it can be inferred that
the pre-test data of both classes were homogenous since 0.772 is higher than 0.05 or 0.772 0.05.
b. Post-test Homogeneity Test After analyzing the homogeneity of pre-test class of experimental class
and control class, then, the writer looked for the homogeneity of post-test class of experimental class and control class by using SPSS v.22. The result
of post-test homogeneity test was described in a table as follows:
Table 4.16 Homogeneity of Post-test Results between Experimental and Control Class
Levene Statistic df1
df2 Sig.
,597 1
84 ,442
Table 4.16 showed that the significance of post-test score between experimental class and control class 0.442. Therefore, it can be concluded that the
post-test data of both classes were homogenous since 0.442 is higher than 0.05. After knowing the data is normal and homogenous, the writer calculated the
data to test the hypothesis that whether there is significant different between students’ reading comprehension of narrative text by using story mapping
technique in experimental class and stud ents’ reading comprehension of narrative
text without story mapping technique in control class by using parametric test. The writer calculated the data using t-test formula. Two classes were compared,
the experiment class was X variable and the controlled class was Y variable. The next table is statistical calculation of the gain score both experimental
class using story mapping technique and control class without story mapping
technique Table 4.17
The Statistical Calculation of the Gain Score of Both the Control and the Experimental Class
Student X Student Y X
Y x
y x²
y²
1 1
24 8
4.66 2.04
21.7156 4.1616
2 2
16 8
-3.34 2.04
11.1556 4.1616
3 3
20 16
0.66 10.04
0.4356 100.8016 4
4 12
8 -7.34
2.04 53.8756
4.1616 5
5 12
20 -7.34
14.04 53.8756 197.1216
6 6
20 4
0.66 -1.96
0.4356 3.8416
7 7
12 4
-7.34 -1.96
53.8756 3.8416
8 8
20 12
0.66 6.04
0.4356 36.4816
9 9
20 8
0.66 2.04
0.4356 4.1616
10 10
12 8
-7.34 2.04
53.8756 4.1616
11 11
32 16
12.66 10.04 160.2756 100.8016
12 12
16 -3.34
-5.96 11.1556
35.5216 13
13 12
16 -7,34
10.04 53.8756 100.8016
Student X Student Y X
Y x
y x²
y²
14 14
16 -3.34
-5.96 11.1556
35.5216 15
15 28
-4 8.66
-9.96 74.9956
99.2016 16
16 12
16 -7.34
10.04 53.8756 100.8016
17 17
24 16
4.66 10.04
21.7156 100.8016 18
18 20
4 0.66
-1.96 0.4356
3.8416 19
19 16
4 -3.34
-1.96 11.1556
3.8416 20
20 16
4 -3.34
-1.96 11.1556
3.8416 21
21 20
4 0.66
-1.96 0.4356
3.8416 22
22 12
-8 -7.34
-13.96 53.8756 194.8816
23 23
16 8
-3.34 2.04
11.1556 4.1616
24 24
8 12
-11.34 6.04 128.5956
36.4816 25
25 28
8 8.66
2.04 74.9956
4.1616 26
26 24
4.66 -5.96
21.7156 35.5216
27 27
32 -4
12.66 -9.96 160.2756
99.2016 28
28 16
16 -3.34
10.04 11.1556 100.8016
29 29
28 12
8.66 6.04
74.9956 36.4816
30 30
8 16
-11.34 10.04 128.5956 100.8016
31 31
12 8
-7.34 2.04
53.8756 4.1616
32 32
32 12.66
-5.96 160.2756 35.5216
33 33
16 8
-3.34 2.04
11.1556 4.1616
34 34
12 16
-7.34 10.04
53.8756 100.8016 35
35 28
4 8.66
-1.96 74.9956
3.8416 36
36 16
16 -3.34
10.04 11.1556 100.8016
37 37
8 8
-11.34 2.04 128.5956
4.1616 38
38 28
12 8.66
6.04 74.9956
36.4816 39
39 24
16 4.66
10.04 21.7156 100.8016
40 40
28 8
8.66 2.04
74.9956 4.1616
41 41
32 16
12.66 10.04 160.2756 100.8016
Student X Student Y X
Y x
y x²
y²
42 42
12 12
-7.34 6.04
53.8756 36.4816
43 43
32 4
12.66 -1.96 160.2756
3.8416
∑ 832
360 2365.771 2100.229
Mean 19.34884 8.372093
55.01793 48.84253
The table 4.17 above described the result calculation of the gained score of the experimental class X and the control class Y. Based on the table above. it can be concluded
that the total score of the experimental class is 832 and the control class is 360.
The process of t-test is as follow: 1. Determining mean of variable X Experimental Class, with formula:
2. Determining mean of variable Y Control Class, with formula:
3. Determining standard of deviation of variable X, with formula: √
√ √
4. Determining standard of deviation of variable Y, with formula: √
√ √
5. Determining standard error of mean variable X, with formula: √
√ √
6. Determining standard error of mean variable Y, with formula: √
√ √
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