Correlations

1. Correlations & correlation studies
• Correlation studies are used by psychologists to find if there is
a systematic and consistent relationship between two
variables.
• A psychologist may observe that there appears to be a
relationship between height and shoe size.
• This observation may be based on a small sample of people.
• To be sure that there is a real and consistent relationship
between height and shoe size they may decide to conduct a
correlational study.

2. What is a correlational analysis?
•A correlational analysis
looks for an association
between two variables
called co-variables.

3. What is a correlational analysis?
• There is no independent
or dependent variable in a
correlation.
• Correlations have two
variables of equal
importance.

4. The variables must be…
•Quantitative data

5. In correlations…
• The strength and direction of an
association between two variables is
measured.
• The direction of correlations can be
categorised into one of these three:
Positive correlation, (+)
Negative correlation, (-)
Zero correlation, (0)

7. In correlations…
• A correlation co-efficient is calculated
that is between -1 and +1 and measures
the direction and strength of the
relationship.
• The direction of the association can be
shown graphically using a scattergram
and the sign before the co-efficient.

8. Correlations & correlation studies

9. Positive Correlation
 There is a relationship
 Both variables increase together.
 A perfect positive correlation has a
co-efficient of +1. This means that
the two variables increase in the
same proportion as each other.
 The closer the correlation
coefficient is to 1, the stronger the
association/relationship between
the two variables.
+

10. Negative Correlation
 There is a relationship
 As one variable increases the other
variable decreases.
 Any other examples?
 A perfect negative correlation has a
co-efficient of -1. . This means that
one variable increases and the
other variable decreases in the
same proportion as each other.

11. Zero Correlation
There is NO clear relationship.
A true zero correlation has a co-efficient of 0.0 This means that there is
absolutely no indication of a relationship between variables.

12. CORRELATIONAL
HYPOSTHESIS
• A hypothesis is a specific,
testable prediction about
what you expect to happen
in your study.
• Correlational hypotheses can
be either a:
Directional (positive)
Directional (negative)
Non-directional
Does not predict the direction
of the outcome
H1

13. Correlation co-efficient strength
indicator
.10 Weak
.30 Moderate
.50 Strong
+/-

15. Activity: Strong or weak?

16. +0.86

17. -0.05

18. -0.92

19. +0.61

20. Correlation does not imply
causation.
• In correlations there is no independent on dependent
variable. The variables that are correlated are of equal
importance.
• Furthermore, correlations can be seen in a similar manner
to natural observations, in the sense that nothing is
manipulated – the variables are simply measured.
• This means that if a significant correlation is found
between two variables, we cannot say that one variable
CAUSED the other because we did not test for that. Such
causal conclusions are unique to experiments.

21. Example - Correlation does not
imply causation

23. Strengths of Correlational Research
Correlations can be easily repeated, which means
that the findings can be confirmed.
Correlations can be used as pilot studies
– If a correlation is significant, then further investigation is
justified.
– If a correlation is insignificant, then a casual relationship
between the two variable can be ruled out.
 Correlations allow us to see trends in data.

24. Limitations of Correlational
Research
 People have a tendency to jump to ‘causal’
conclusions, which can lead to the misinterpretation
of results.
 Intervening variables – some correlational analyses
fail to consider other variables that can explain why
the co-variables being studied are linked.