Correlational ResearchResearch Methodology

Prepared By

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Manu Melwin JoyAssistant Professor

Ilahia School of Management Studies

Kerala, India.Phone – 9744551114

Mail – manu_melwinjoy@yahoo.com

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.

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.

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.

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.

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.

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.

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).

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.

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.

Limitations

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.