39
most is 66. It means that most of the students obtained 66 in speaking. The standard deviation is 10 with variance 113.
Seeing the scores above, it can be concluded that some students of the 3
rd
semester of EED still speak little. Some students are excellent and most of them are passive. It can be seen that most of students obtained
score 66, in which score 66 is characterized as C. Although some students still obtained C, there are some students who really good in their speaking
performance. Overall, the 3
rd
students of EED of UIN are still passive in speaking. They still want not to speak up and choose to give no
participation in speaking in group, although there are some students who are very excellent in their speaking performance.
B. Data Analysis
To analyze the data above, the researcher used the formula of “r” Pearson product moment. Before doing the calculation, the data were
described such as bellow:
Table 4.6 Data Analysis Table
Participants X
Y XY
X
2
Y
2
Student 1 75
86 6450
5625 7396
Student 2 71
70 4970
5041 4900
Student 3 79
86 6794
6241 7396
Student 4 60
74 4440
3600 5476
Student 5 81
68 5508
6561 4624
Student 6 70
76 5320
4900 5776
Student 7 71
50 3550
5041 2500
Student 8 74
66 4884
5476 4356
Student 9 82
70 5740
6724 4900
Student 10 70
60 4200
4900 3600
Student 11 72
74 5328
5184 5476
Student 12 78
84 6552
6084 7056
Student 13 73
66 4818
5329 4356
Student 14 69
66 4554
4761 4356
40
Student 15 83
94 7802
6889 8836
Student 16 77
86 6622
5929 7396
Student 17 75
58 4350
5625 3364
Student 18 78
70 5460
6084 4900
Student 19 70
56 3920
4900 3136
Student 20 74
68 5032
5476 4624
Student 21 79
80 6320
6241 6400
Student 22 66
64 4224
4356 4096
Student 23 73
76 5548
5329 5776
Student 24 85
78 6630
7225 6084
Student 25 85
66 5610
7225 4356
Student 26 76
82 6232
5776 6724
Student 27 85
94 7990
7225 8836
Student 28 77
80 6160
5929 6400
Student 29 65
68 4420
4225 4624
Student 30 74
64 4736
5476 4096
Student 31 77
76 5852
5929 5776
N = 31
Σ
X=2324
Σ
Y=2256
Σ
XY=170016
Σ
X
2
=175306
Σ
Y
2
=167592 Formula:
r
xy =
Σ Σ
Σ [
][ Σ
]
Description:
N = Number of Participants
X = Students’ Listening Comprehension Scores
Y = Students’ Speaking Scores
∑ X = The Sum Scores of Listening Comprehension
∑ Y = The Sum Scores of Speaking
∑ XY = The Sum of Multiplied Score between X and Y ∑ X
2
= The Sum of the Squared Scores of listening comprehension
∑ Y
2
= The Sum of the Squared Scores of Speaking
Calculation:
N = 31
X = 2324
41
Y = 2256
XY = 170016 X
2
= 175306 Y
2
= 167592
r
xy
=
Σ Σ
Σ [
][ Σ
]
=
. .
² [ .
²]
=
[ ][
]
=
[ ][
]
= =
.
= 0.46 To make sure the result of the calculation above, the researcher used
SPSS program. The using of SPSS is to know whether the calculation that the researcher did manually was correct and to make sure that there is no
mismatching calculation between scores that the researcher counted. The calculation of SPSS was described such as follow:
Table 4.7 SPSS Correlation Table
Listening Speaking
Listening Pearson
Correlation 1
.46 Sig. 2-tailed
.009 N
31 31
Speaking Pearson
Correlation .46
1 Sig. 2-tailed
.009
42
N 31
31 . Correlation is significant at the 0.01 level 2-
tailed.
The Pearson correlation above means from the 31 respondents was found the correlation between two variables r
xy
0.46, which means the correlation is positive or there is a correlation between two variables
listening comprehension and speaking ability. The results of those two calculations manual calculation and SPSS
calculation are the same. The correlation value analyzed by SPSS is r
xy
0.46. It means that there is no mismatch in the process of calculating the data.
After finding the “r” correlation score, the next step to do is to find the significance of variables by calculating r
xy
is tested by significance test formula:
Formula:
t
count
=
²
Description:
t
count
= t value r
= 0.46 n
= 31
Calculation:
t
count
=
²
=
. .
²
=
. .
=
. .
.
=
. .
= 2.829
43
Before testing the t
count
, the writer made two hypotheses of significance; they are:
H
a
: There is significant correlation between two variables H
o
: There is no significant correlation between two variables The formulation of test:
1. If t
o
t
table
, it means that the null hypothesis is rejected and there is significant correlation.
2. If t
o
t
table
, the null hypothesis is accepted and there is no significant correlation.
Based on the calculation above, the result is compared by t
table
in the significant of 1 and n=31, the writer found the Degree of Freedom Df with
the formula: Df = N – nr
= 31- 2 = 29
From Df = 29, it is obtained t
table
of 1 = 2.76. It indicates that t
o
t
table
, in which 2.829 2.76. Therefore, the alternative hypothesis H
a
is accepted. In other words, there is a significant correlation between listening
comprehension and speaking ability.
C. Data Interpretation
