2. DEFINITION
Correlation refers to a technique used to
measure the relationship between two or
more variables.
A correlation coefficient is a statistical
measure of the degree to which changes to
the value of one variable predict change to
the value of another.
A correlation can only indicate the presence
or absence of a relationship, not the nature
of the relationship. Correlation is not
causation.
3. CORRELATION COEFFICIENT FORMULA:
OVERVIEW.
Correlation coefficient formulas are used to
find how strong a relationship is between
data. The formulas return a value between
-1 and 1, where:
1 indicates a strong positive relationship.
-1 indicates a strong negative
relationship.
A result of zero indicates no relationship
at all.
5. POSITIVE CORRELATION
Association between variables such that high scores
on one variable tend to have high scores on the other
variable
A direct relation between the variables
6. NEGATIVE CORRELATION
Association between variables such that high scores on
one variable tend to have low scores on the other
variable.
An inverse relation between the variables
8. SPSS VS HAND CALCULATION
X Y XY X2 Y2
0 8 0 0 64
2 10 20 4 100
3 4 12 9 16
6 6 36 36 36
9 1 9 81 1
10 3 30 100 9
30 32 107 230 226
N ∑XY - ∑X ∑Y
r =
[ N ∑X2 – (∑X)2] [N ∑Y2 – (∑Y)2]
(6 X 107) – 30 (32)
[6 (230) – 302] [6 (226) – 322 ]
r = -.797 (note cross
products term in the
numerator is negative)
and R-square = .635
9. SPSS VS HAND CALCULATION
Correlations
1 -.797*
.029
6 6
-.797* 1
.029
6 6
Pearson Correlation
Sig. (1-tailed)
N
Pearson Correlation
Sig. (1-tailed)
N
Shyness
Speeches
Shyness Speeches
Correlation is significant at the 0.05 level (1-tailed).*.