Table 4.10 Table of Frequency Distribution of Post Test Result of Controlled Class
Control
Frequency Percent
Valid Percent Cumulative
Percent Valid
44 2
2.7 5.4
5.4 46
1 1.4
2.7 8.1
47 2
2.7 5.4
13.5 48
1 1.4
2.7 16.2
55 1
1.4 2.7
18.9 59
2 2.7
5.4 24.3
60 4
5.4 10.8
35.1 62
3 4.1
8.1 43.2
65 4
5.4 10.8
54.1 66
4 5.4
10.8 64.9
68 3
4.1 8.1
73.0 69
1 1.4
2.7 75.7
70 1
1.4 2.7
78.4 71
1 1.4
2.7 81.1
72 1
1.4 2.7
83.8 74
1 1.4
2.7 86.5
75 1
1.4 2.7
89.2 79
1 1.4
2.7 91.9
80 1
1.4 2.7
94.6 83
1 1.4
2.7 97.3
85 1
1.4 2.7
100.0 Total
37 50.0
100.0 Missing
System 37
50.0 Total
74 100.0
Before the writer calculated the value of t-test to look at the hypothesis, the writer had to analyze the normality and homogeneity of the data. The examination
of normality was needed to know whether the data had been normally distributed. Then, after getting the normality, the next step was calculating the homogeneity of
data. It was proposed to look at whether the data was homogeneous or heterogeneous.
3. Normality Test
The normality test is performed using Kolmogorov Smirnnov and Shapiro- Wilk. The test is for the two groups, both post-test and pre-test group, to
determine if the distribution of the data from the sample is normal. Thus, the researcher used SPSS version 22 software. If the normality is more than the level
of significance α 0.05, scores will be normally distributed.
Table 4.11 Normality Pre-test Results between Experimental and Controlled Class
Tests of Normality
Kelas Kolmogorov-Smirnov
a
Shapiro-Wilk Statistic
df Sig.
Statistic df
Sig. Pretest
Experiment .143
37 .054
.957 37
.160 Control
.111 37
.200 .933
37 .027
. This is a lower bound of the true significance. a. Lilliefors Significance Correction
Table 4.12 Normality Post Test Results between Experimental and Controlled Class
Tests of Normality
Kelas Kolmogorov-Smirnov
a
Shapiro-Wilk Statistic
df Sig.
Statistic df
Sig. Posttest
Experiment .130
37 .118
.929 37
.021 Control
.108 37
.200 .966
37 .319
. This is a lower bound of the true significance. a. Lilliefors Significance Correction
In normality test based on Kolmogorov-Smirnov, data were stated as distributed normal when sig. score was above 0.05. In the table above, it showed
that both experimental and controlled class had normal distribution data. The sig. score in pre-test in controlled and experimental class were 0.054 and 0.200.
Meanwhile the sig. score in post-test between both of the class were 0.118 and 0.200.
4. Homogeneity Test
Homogeneity test is used to test whether the data from the two groups have the same variant in order that the hypotheses can be tested by t-test. Like
normality test, this kind of test also uses SPSS version 22 software. Homogeneity test was calculated by using Levine. The following tables contained the result of
test of homogeneity between both of the class.
Table 4.13 Homogeneity Pre-test Result between Experimental and Controlled
Class
Test of Homogeneity of Variances
Pretest Levene Statistic
df1 df2
Sig. .098
1 72
.755
Table 4.14 Homogeneity Post Test Result between Experimental and Controlled
Class
Test of Homogeneity of Variances
Posttest Levene Statistic
df1 df2
Sig. 3.421
1 72
.068
In the test of homogeneity, data were stated as homogeny distribution when sig. score was above 0.05. Sig. Score in these columns were 0.755 and 0.068.
These are bigger than 0.05 which means that these data had homogeny distribution data.
5. Hypothesis Testing
In this part, the writer calculated the data to test the hypothesis that whether there was effectiveness on stud
ents’ writing of recount text in experimental class which used pictures and stud
ents’ writing of recount text in controlled class without pictures. 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 formula of T-test was expressed as follows:
Here is the table of calculation between experimental class and controlled class:
Table 4.15 The Comparison of Gained Score between Students in Experimental
Class and Students in Controlled Class
No. Eks X
ctrl Y x=Mx-X
y=My-Y x²
y² 1
12 7
-7.78 -4.35
60.53 18.92
2 12
4 -7.78
-7.35 60.53
54.02 3
14 5
-5.78 -6.35
33.41 40.32
4 32
10 12.22
-1.35 149.33
1.82 5
22 12
2.22 0.65
4.93 0.42
6 34
-3 14.22
-14.35 202.21
205.92 7
2 12
-17.78 0.65
316.13 0.42
8 32
-19.78 20.65
391.25 426.42
9 9
16 -10.78
4.65 116.21
21.62 10
31 3
11.22 -8.35
125.89 69.72
11 25
13 5.22
1.65 27.25
2.72 12
5 26
-14.78 14.65
218.45 214.62
13 13
21 -6.78
9.65 45.97
93.12 14
20 3
0.22 -8.35
0.05 69.72
15 28
12 8.22
0.65 67.57
0.42 16
15 26
-4.78 14.65
22.85 214.62
17 40
9 20.22
-2.35 408.85
5.52 18
26 9
6.22 -2.35
38.69 5.52
19 17
19 -2.78
7.65 7.73
58.52 20
21 19
1.22 7.65
1.49 58.52
21 24
6 4.22
-5.35 17.81
28.62 22
13 14
-6.78 2.65
45.97 7.02
23 31
19 11.22
7.65 125.89
58.52 24
28 7
8.22 -4.35
67.57 18.92
25 34
17 14.22
5.65 202.21
31.92 26
11 17
-8.78 5.65
77.09 31.92
27 37
-2 17.22
-13.35 296.53
178.22 28
31 17
11.22 5.65
125.89 31.92
29 23
13 3.22
1.65 10.37
2.72
30 10
9 -9.78
-2.35 95.65
5.52 31
32 14
12.22 2.65
149.33 7.02
32 13
8 -6.78
-3.35 45.97
11.22 33
22 3
2.22 -8.35
4.93 69.72
34 8
6 -11.78
-5.35 138.77
28.62 35
9 1
-10.78 -10.35
116.21 107.12
36 17
6 -2.78
-5.35 7.73
28.62 37
11 10
-8.78 -1.35
77.09 1.82
∑ 732
420 0.14
0.05 3904.27 2212.43
Mean 19.78
11.35 From Table 4.15, it could be seen that the average of gained score of
experimental class was higher than controlled class. It meant that there was effectiveness of using pictures in experimental class in students’ writing of
recount text. The data were calculated based on the step of the test. The formulation as
followed: 1. Determining mean of variable XM
x
, with the formula:
2. Determining
1
mean of variable YM
y
, with the formula:
3. Determining of standard of deviation XSD
x
, with the formula: √
√ √
4. Determining of standard of deviation YSD
y
, with the formula:
√ √
√
5. Determining of standard errors mean of variable XSE
mx
, with the formula: √
√
