Correlational research explores the relationship between two variables, identifying how changes in one may predict changes in another, without establishing causation. The strength and direction of these relationships are quantified by a correlational coefficient, which ranges from -1 to +1. However, it is crucial to remember that correlation does not imply causation, as external factors can influence both variables.

1. Correlational Research
Research Methodology

2. Prepared By
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Manu Melwin Joy
Assistant Professor
Ilahia School of Management Studies
Kerala, India.
Phone – 9744551114
Mail – manu_melwinjoy@yahoo.com

3. Correlational Research
• A correlation is simply
defined as a relationship
between two variables.
The whole purpose of
using correlations in
research is to figure out
which variables are
connected.

4. Correlational Research
• This simple definition is
the basis of several
statistical tests that result
in a correlation
coefficient, defined as a
numerical representation
of the strength and
direction of a relationship.

5. Correlational Research
• Correlation research is
looking for variables that
seem to interact with each
other, so that when you can
see one changing, you have
an idea of how the other will
change. This often entails the
researcher using variables
that they can't control.

6. Direction of a Correlation
• Positive Correlation: when
two variables go in the SAME
direction. For example,
domestic violence and
bowling. When bowling goes
up, so does domestic
violence. When domestic
violence decreases, so does
bowling.

7. Direction of a Correlation
• Negative Correlation: here the two
variables go in DIFFERENT
directions. For example,
consumption of garlic and dating
(now I am making this one up). The
less garlic you eat, the more you
date. The more garlic you eat, the
less the date. One variable going in
one direction can be used to predict
the other variable going in the
opposite direction.

8. Correlational Coefficient
• Scientists measure the
strength of a correlation by
using a number called a
correlational coefficient. Now
you do not have to know how
they get the number, but you
should know what it means
when you see it. The number
range from -1 to +1.

9. Correlational Coefficient
• If two variables (like studying and
grades) have a correlation above
zero (like +.76) then you have a
positive correlation and the more
you study, the better grades you
have. The the number is below
zero (like -.42) then you have a
negative correlation and when
one variable goes up the other
goes down (like garlic and dating).

10. Correlational Coefficient
• If two variables have a correlation
of zero then they have NO
relationship with each other. The
closer the numbers go to either +1
or -1, the stronger the
correlation. The strength has
nothing to do with whether the
number is positive of negative. A
correlation of -.88 is stronger than
one that is +.56. the closer the
number gets to zero (whether
positive or negative), the weaker
the correlation.

11. Limitations
• It is very important to
remember that correlation
doesn't imply causation
and there is no way to
determine or prove
causation from a
correlational study. This is a
common mistake made by
people in almost all
spheres of life.

12. Limitations

13. Limitations
• For example, a US politician speaking
out against free lunches to poor kids
at school argues -“You show me the
school that has the highest free and
reduced lunch, and I'll show you the
worst test scores, folks”
(nymag.com). This is a correlation he
is speaking about - one cannot imply
causation. The obvious explanation
for this is a common cause of
poverty: people who are too poor to
feed their children will not have the
best test scores.