29
To test the speaking, the researcher used role play for the test. The students were asked to make groups consisted of 4 people. Then,
they were asked to conduct conversation using the topics that were given to each group.
3. Video To be more detail in assessing the ability of speaking, the
researcher initiated to take a video of the students when they attended the speaking test. Moreover, this step of data collection was used to help the
assessors easier to handle the assessment. The video was used to assess and to analyze their speaking in detail, because it can be replied anytime
and give some spaces to the assessors to understand and consider their speaking ability.
F. Technique of Data Analysis
In analyzing the data, the researcher uses correlation product moment which developed by Carl Pearson because the researcher wants to find out the
influence which is related to correlational study. “Correlation product moment is used to show whether there is a correlation or relationship between
X variable and Y variable.”
6
The symbol of the correlation product moment is “r”.
7
Data operation technique is done through the steps below: a. Finding the number of correlation using formula:
r
xy
=
Σ Σ
Σ [
][ Σ
]
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
6
http:eprints.undip.ac.id66081Korelasi_Product_Moment.pdf
7
Sudijono, Op. cit., p.27.
30
∑ X
2
= The Sum of the Squared Scores of listening comprehension
∑ Y
2
= The Sum of the Squared Scores of Speaking ∑ XY = The Sum of Multiplied Score between X and Y
This formula is used in finding index correlation “r” product moment between X variable and Y variable r
xy
b. To know the significance between two variables, the formula of the significance test is:
8
t
count
=
²
t
count
= t value r
= value of correlation coefficient n
= number of participants c. To interpret the index scores of “r” correlation, product moment
r
xy
usually used the interpretation such as bellow:
9
Table 3.1 Pearson Correlation
The score of “r” product moment r
xy
Interpretation
0.00 – 0.19 There is a correlation between X and Y,
but the correlation is very weak or little so it is ignored or it is considered no
correlation in this rating. 0.20 – 0.39
There is a correlation between X and Y, but it is weak or little.
0.40 – 0.69 There is a correlation between X and Y.
The value is medium. 0.70 – 0.89
There is high correlation between X and
8
Ridwan and H. Sunarto, Pengantar Statistika Pendidikan, Sosial, Ekonomi, Komunikasi, danBisnis, Bandung: Alfabeta, 2011, p.81.
9
Ibid.
31
Y. 0.90 – 1.00
There is a very high correlation between X and Y.
G. Statistical Hypotheses
