Correlational research refers to a non-experimental research method which studies the

relationship between two variables with the help of statistical analysis. Correlational research design
does not study the effects of extraneous variables on the variables under study. Correlational research
is a type of non-experimental research method in which a researcher measures two variables,
understands and assesses the statistical relationship between them with no influence from any
extraneous variable. Correlational research is a type of research method that involves observing two
variables in order to establish a statistically corresponding relationship between them. The aim of
correlational research is to identify variables that have some sort of relationship do the extent that a
change in one creates some change in the other.

Correlation means that there is a relationship between two or more variables, but this
relationship does not necessarily imply cause and effect. When two variables are correlated, it simply
means that as one variable changes, so does the other. We can measure correlation by calculating
a statistic known as a correlation coefficient. A correlation coefficient is a number from -1 to +1
that indicates the strength and direction of the relationship between variables. The correlation
coefficient is usually represented by the letter r.

What Is a Correlation Coefficient?

The correlation coefficient is a measure of the correlation strength. It can range from –1.00
(negative) to +1.00 (positive). A correlation coefficient of 0 indicates no correlation.

The number portion of the correlation coefficient indicates the strength of the relationship.
The closer the number is to 1 (be it negative or positive), the more strongly related the variables are,
and the more predictable changes in one variable will be as the other variable changes. The closer
the number is to zero, the weaker the relationship, and the less predictable the relationships between
the variables becomes. For instance, a correlation coefficient of 0.9 indicates a far stronger
relationship than a correlation coefficient of 0.3. If the variables are not related to one another at all,
the correlation coefficient is 0. The example above about ice cream and crime is an example of two
variables that we might expect to have no relationship to each other.

The sign—positive or negative—of the correlation coefficient indicates the direction of the
relationship.

The correlation coefficient shows the correlation between two variables (A correlation coefficient
is a statistical measure that calculates the strength of the relationship between two variables), a value
measured between -1 and +1. When the correlation coefficient is close to +1, there is a positive
correlation between the two variables. If the value is close to -1, there is a negative correlation
between the two variables. When the value is close to zero, then there is no relationship between
the two variables.

Consider hypothetically; a researcher is studying a correlation between cancer and marriage. In this
study, there are two variables: disease and marriage. Let us say marriage has a negative association
with cancer. This means that married people are less likely to develop cancer.
Types of correlational Method

Mainly three types of correlational research have been identified:

1. Positive correlation: A positive relationship between two variables is when an increase in one
variable leads to a rise in the other variable. A positive correlation means that the variables move
in the same direction. Put another way, it means that as one variable increases so does the other,
and conversely, when one variable decreases so does the other. A decrease in one variable will see
a reduction in the other variable. For example, the amount of money a person has might positively
correlate with the number of cars the person owns.

2. Negative correlation: A negative correlation is quite literally the opposite of a positive

relationship. A negative correlation means that the variables move in opposite directions. If two
variables are negatively correlated, a decrease in one variable is associated with an increase in the
other and vice versa.If there is an increase in one variable, the second variable will show a decrease
and vice versa.

For example, being educated might negatively correlate with the crime rate when an increase in one
variable leads to a decrease in another and vice versa. If the level of education in a country is
improved, it can lower crime rates. Please note that this doesn’t mean that lack of education leads
to crimes. It only means that a lack of education and crime is believed to have a common reason –
poverty.

3. No correlation: In this third type, there is no correlation between the two variables. A change in
one variable may not necessarily see a difference in the other variable. For example, being a
millionaire and happiness is not correlated. An increase in money doesn’t lead to happiness.
 Characteristics of correlational

Correlational research has three main characteristics. They are:

• Non-experimental: Correlational study is non-experimental. It means that researchers need not

manipulate variables with a scientific methodology to either agree or disagree with a hypothesis.
The researcher only measures and observes the relationship between the variables, without
altering them or subjecting them to external conditioning.
• Backward-looking: Correlational research only looks back at historical data and observes events
in the past. Researchers use it to measure and spot historical patterns between two variables. A
correlational study may show a positive relationship between two variables, but this can change in
the future.
• Dynamic: The patterns between two variables from correlational research are never constant and
are always changing. Two variables having a negative correlation in the past can have a positive
correlation relationship in the future due to various factors.

There are two methods in which data is collected in a correlational study:

Naturalistic observation: In naturalistic observation, the participants of the study are observed in
their natural environments. Naturalistic observation is a kind of field study. The researcher can observe
participants in grocery stores, cinemas, playgrounds, schools, etc.

Researchers who use naturalistic observation as a means of data collection observe individuals as
unobtrusively as possible. This is because they don’t want the participants to be aware of being observed
as it may influence their behavior and they may not be their natural self. For instance, if the researcher
is observing consumers in a grocery store and the kind of items they usually buy, it is ethically acceptable
as participants know that they are subjected to being observed in public spaces. The data collected in
naturalistic observation can be qualitative or quantitative.

Archival data: Archival data is another way to collect data for correlational research design. This type
of data has been collected previously by doing similar studies. Archival data is usually collected through
primary research. Archival data tends to be more straightforward as compared to the data collected
through naturalistic observation.