Research Finding RESEARCH FINDING AND INTERPRETATION
17 Student 17
60 18
Student 18 80
19 Student 19
78 20
Student 20 80
21 Student 21
88 22
Student 22 70
23 Student 23
85 24
Student 24 76
25 Student 25
50 26
Student 26 68
27 Student 27
60 28
Student 28 80
29 Student 29
75 30
Student 30 76
31 Student 31
85 32
Student 32 80
33 Student 33
60 34
Student 34 72
35 Student 35
82 36
Student 36 85
37 Student 37
85 38
Student 38 82
39 Student 39
85 40
Student 40 82
2. The Analysis of Data
The next steps after scoring each variable, the write calculate the data using t-test formula.
To gain the formula, the writer divided the data into two according to their attendance in English language course.
Table 4.3 List of Students’ score classification in English language course attendance
No 70
Y1X1 70
Y2X2 Y1
2
X1
2
Y2
2
X2
2
1 88
82 7744
6724 2
70 76
4900 5776
3 85
80 7225
6400 4
76 66
5776 4356
5 50
58 2500
3364 6
68 56
4624 3136
7 60
62 3600
3844 8
80 55
6400 3025
9 75
60 5625
3600 10
76 62
5776 3844
11 85
75 7225
5625 12
80 65
6400 4225
13 60
52 3600
2704 14
72 68
5184 4624
15 82
60 6724
3600 16
85 65
7225 4225
17 85
60 7225
3600 18
82 80
6724 6400
19 85
78 7225
6084 20
82 80
6724 6400
Total 1526
1340 118426
91556
From the table above we can get some number to gain the formula of t-est.
t
̅ ̅
√
Before we calculated the t formula, we have to find the SS score, to find the score of SS, we used the formula as follow;
SS
1
∑
∑
or
SS
2
∑
∑
Firstly we find the SS
1
according to formula as follow.
SS
1
∑
∑
= 118426 – 86433,8
= 1992.2
After that we find the SS
2
according to formula as follow.
SS
2
∑
∑
= 915566 – 89780
= 1776 And now we have everything to fill out on the formula to find the t-score.
After that we substitute the number for each symbol of the formula.
t
√
√
√
√
From the result of the calculation, indicates that the result of t-score is 2.952 and after that we calculate the degree of freedom, the formula as follow:
df = N – 2
= 40 – 2
= 38
After the calculation of the t-formula and knowing the degrees of freedom then we compared it with t-table with the degrees of freedom 38, the significance
level that used is in the level 1 and 5 . And the score of the significance level in 1 and 5 is as follow:
- Significant level 1 = 2.423
- Significant level 5 = 1.684
So that, the result of t-table in 1 2.423, can be seen that t-result t-table = 2.952 2.423 and in 5 scale is 1.684, then in this scale t-result t-table = 2.952
1.684. We know that t is higher than t-table in both level 1 and 5. After we know the difference between the students who always attend the
English language course and the students who rarely attend the course then the writer continue to know is there any correlation between English language course
attendance and students’ achievement in English language learning in the classroom. And the correlation of them is presented on the table as follow:
Table 4.4 Students’ Correlation Score
No Kehadiran
Nilai XY
X
2
Y
2
X S.2 Y
1 63
82 5166
3969 6724
2 13
76 988
169 5776
3 38
80 3040
1444 6400
4 38
66 2508
1444 4356
5 44
58 2552
1936 3364
6 44
56 2464
1936 3136
7 50
62 3100
2500 3844
8 50
55 2750
2500 3025
9 56
60 3360
3136 3600
10 56
62 3472
3136 3844
11 56
75 4200
3136 5625
12 56
65 3640
3136 4225
13 63
52 3276
3969 2704
14 63
68 4284
3969 4624
15 63
60 3780
3969 3600
16 63
65 4095
3969 4225
17 63
60 3780
3969 3600
18 69
80 5520
4761 6400
19 69
78 5382
4761 6084
20 69
80 5520
4761 6400
21 75
88 6600
5625 7744
22 75
70 5250
5625 4900
23 75
85 6375
5625 7225
24 75
76 5700
5625 5776
25 81
50 4050
6561 2500
26 81
68 5508
6561 4624
27 81
60 4860
6561 3600
28 81
80 6480
6561 6400
29 81
75 6075
6561 5625
30 88
76 6688
7744 5776
31 88
85 7480
7744 7225
32 88
80 7040
7744 6400
33 88
60 5280
7744 3600
34 88
72 6336
7744 5184
35 88
82 7216
7744 6724
36 88
85 7480
7744 7225
37 88
85 7480
7744 7225
38 88
82 7216
7744 6724
39 88
85 7480
7744 7225
40 88
82 7216
7744 6724
2759 2866
200687 203059
209982
r
xy=
∑ ∑
∑ √
∑ ∑
∑ ∑
√ ∑
√ √
√
r
xy
=
0,40
The next step is to know that the correlation between them is significant or not
, therefore the result of calculation “r” is compared with the “r” table. Before we compared it, we should know “df” or “db” according to the rule df=N-nr. The
respondents of this research are 40 and there are two variable. So, N=40, and nr=2.
df = N-nr df
=40-2 = 38
According to the calculation be fore, “df” of this research is 38.
In “r-table” of significant level 1 and 5 of 38 are: Significant level 1 = 0.413
Significant level 5 = 0.320
As we know from the calculation above, in the level of significance 5 the
score of “r
xy”
or “r” is significant because “r
xy
r
table
”, but in the level significance 1 is insignificant
“r
xy
r
table
”. The score of the r
xy
is 0.40 and r
table
in significance level 1 is 0.413, and the result is as 0.40 0.413, the r
xy
is lower than r
table.
And in the significance level 5 r
table
is 0.320, and the result is 0.40 0.320, mean the r
xy
is higher than r
table.
After doing the hypothesis testing, then we should know the coefficient of determination with r = 0,40, because in th
e simple implementation before in r” product moment between 0,40
– 0,700, r
xy
= 0,40, means that between X variable and Y variable has enough correlation . To know how much the influences of X to
Y, we used coefficient of determination formula with r = 0,40.
KD = r
xy 2
X 100 = 0,40
2
X 100 = 0,16 X 100
= 16
From the calculation of coefficient of determination abo ve, “KD” of this
research is 16 , means that the attendance of the students in English language course only has the influence 16
to the students’ achievement in English language course, and there are 84 from the other aspect that can influence their
achievement in English Language Learning.