Review of Previous Study
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significance of the correlation between those variables, that is variable X and variable Y.
Correlation coefficient usually represented by r is index indicating both the direction of the correlation either positive or negative and the degree of
the relationship between variables. Correlational coefficients can rangefrom - 1.00 to +1.00 with positive numbers used to identify a positive relationship
and negative numbers being used to identify a negative relationship.The following table can be used todetermine the strength of a relationship:
Table 3.1 Simple Interpretation of Correlation
Rxy Interpretation
0.00 0.20 There is correlation between X variable and Y variable,
but it is very week or very low. So the correlation is rejected. In other words, there is no correlation between
X variable and Y variable. 0.20 0.40
There is week or low correlation between X variable and Y variable but it is sure.
0.40 0.70 There is an enough correlation between X variable and
Y variable. 0.70 0.90
There is a strong or high correlation between X variable and Y variable.
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0.90 1.00 There is a very strong or very high correlation between
X variable and Y variable.
From the explanation above, we can identify that the first variable is -assessment level which is taken by distributing questionnaire; it
is considered as independent variable variable X. The second variable is English learning achievement score which is taken by collecting secondary
data of final test score in first semester; it is considered as dependent variable variable Y.
In this study, the researcher cannot directly manipulate the independent variable because there is no control group as in experimental
research and also no treatment given since the independent variable occur naturally.