31 questionnaire. Close-ended questionnaire is a questionnaire which specifically, the
questionnaire used in this study asks about the kind of online games, how many hours and how long they play online games.
E. Data Analysis Techniques
According to Wiersma 1995, “data could take many forms, and when a data
take numerical forms such as scores or frequencies, the usual course of action is to perform an appropriate type of statistical analysis
” p.337. The choice of the data analysis technique depended on several factors such as the type of variable, the
nature of variable, the shape of the distribution of a variable, and the study design adopted to collect information about the variables. The researcher used a statistic
calculation to analyze the data. Correlation statistic is the best choice for the researcher to analyze the data since the researcher wants to know about the
relationship between the frequency of playing the game by the gamer students and the score of vocabulary test to find the influence of the online games.
The researcher assumed a linear relationship between the two variables which were frequency of playing online games and the score of vocabulary test. This
relation could be analyzed using the Pearson product moment. Pearson product moment is a formula for finding the correlation between x and y expressed as a
number Deauna, 1996. Besides using Pearson product moment, the researcher looked for the influence of online games on students’ vocabulary mastery by
analyzing the mean score of each non-gamer and gamer students’ scores. The mean
scores became the standard score of each variable non-gamer students and gamer students. It was used to know the vocabulary mastery of non-gamer and gamer
32 students. The formula to find the correlation coefficient by the Pearson product
moment and the mean of the vocabulary test score is showed below.
Pearson Product Moment:
= ∑
�
− ̅
�
− ̅
�=1
− =
∑ −
�
= any x value ̅ = mean of x
�
= any y value ̅ = mean of y
= standard deviation of x = standard deviation of y
= number of pairs of x and y = standard score for x
= standard score for y
Mean Score:
̅ =
∑
̅ = mean of m ∑ = sum of m
= number of m Based on Siregar 2013, the correlation between two variables can be known
through the coefficient of correlation. Positive correlation appears if the coefficient is close to +1, while negative correlation appears if the coefficient of correlation is
close to -1. There is no correlation if the coefficient of correlation is 0. There are some ways to measure the correlation between variables. Pearson
product moment was chosen to analyze the data because Pearson product moment
