Population and Sample The Relationship Between Intelligence Quotient (IQ) and Students' Achievement on Extensive Reading
in which:
r
xy
:the correlation coefficient between Extensive Reading achievement scores and Intelligence Quotient IQ scores
N : the number of respondent
X :
the student’s score in Intelligence Quotient IQ Y
: the student’s score in reading achievement
ΣX : the sum of Intelligence Quotient IQ scores ΣY : the sum of Extensive Reading achievement scores
ΣX
2
: the sum of squares of Intelligence Quotient IQ scores ΣY
2
: the sum of squares of Extensive Reading achievement scores ΣX
2
: the squares of the sum of Intelligence Quotient IQ scores ΣY
2
: the squares of the sum of Extensive Reading achievement scores ΣXY : the sum multiple of Intelligence Quotient IQ scores and Extensive
Reading achievement scores Then, the contribution of the independent variable x towards the
dependent variable y is investigated through the determination coefficient r
2
as follows:
4
R : value of determinant coefficient r
2
:value of the squared correlation coefficient Moreover, after getting the r score, the significance between two variables
will be tested to know the correlation between variable X and variable Y. The formula of the significance test is:
5
4
Ibid, 2013, p. 125.
5
Sugiyono, Metode Penelitian Kuantitatif, Kualitatif dan R D, Bandung: Alfabeta, 2013, p. 187.
R = r
2
x 100
t
count
=
t : t value
r :value of correlation coefficient n : number of sample
With that formula, the writer got r coefficient that can describe the correlation between X variable and Y variable, as below:
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Table 3.1 The Interpretation of Correlation
Interpretation
0.00 – 0.20 Slight: almost negligible relationship.
0.20 – 0.40 Low correlation; definite but small relationship.
0.40
– 0.70 Moderate correlation; substantial relationship.
0.70 – 0.90 High correlation; marked relationship.
0.90 – 1.00 Very high correlation; very dependable relationship.
Adopted from Guilford, 1956.