Questionnaire Documentation Instrument and Technique of Data Collection
To draw conclusions from the data obtained, the writer used several steps:
1. Linearity test aims to determine whether the two variables had a
significant linear relationship or not. This test is required in the correlational analysis.
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The variance analysis of ANOVA Table is used in this study.
2. Cronbach’s Alpha to determine whether the data populations are normally
distributed or not. If the data are normally distributed, the next step is implementing Pearson Product Moment r.
3. Pearson Product Moment r is used to find out whether there is a
significant correlation between students’ anxiety and their achievement in learning English. The formulation of the Pearson Product Moment such as
follow:
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r =
–
In which:
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Budi Susetyo, Statistika untuk Analisis Data Penelitian, Bandung: PT Refika Aditama, 2010, p. 170.
11
Bernard C. Beins, Op.cit., p. 287.
r N
∑X ∑Y
∑XY ∑X
2
∑Y
2
= the correlation coefficient score = number of sample
= the sum of total score in variable X = the sum of total score in variable Y
= the sum of multiply score of variable X and Y = the sum of the squared score in variable X
= the sum of the squared score in variable Y
This formula is commonly applied to find index correlation “r”
product moment between variable X and variable Y if it is manually computed.
4. Then, to know the coefficient of determination which represents the
percentage contribution of X variable to Y variable, it can be known by this formula:
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R = r
2
x 100
In which: R
= value of determinant coefficient r
2
= value of the squared correlation coefficient
5. The next step is finding the significance between two variables, the
formula of the significant test is:
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t
test
=
In which:
6. The last step is interpreting the index scores of “r” correlation, r value r
o
usually used the interpretation such as bellow, regardless of positive or negative sign:
12
Budi Susetyo, Op.cit., p. 122.
13
Ibid., p. 182.
t
test
r n
= t value = the result of correlation coefficient
= number of sample