Correlational research: definition with example
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.
Our minds can do some brilliant things. For example, it can memorize the jingle of a pizza truck. Louder the jingle, the closer the pizza truck is to us. Who taught us that? Nobody! We relied on our understanding and came to a conclusion. We don’t stop there, do we? If there are multiple pizza trucks in the area and each one has a different jingle, we would memorize it all and relate the jingle to its pizza truck.
This is what correlational research precisely is, establishing a relationship between two variables, “jingle” and “distance of the truck” in this particular example. The correlational study is looking for variables that seem to interact with each other. When you see one variable changing, you have a fair idea of how the other variable will change.
Correlational research example
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.
Let us take an example to understand correlational research.
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.
However, this doesn’t necessarily mean that marriage directly avoids cancer. In correlational research, it is not possible to establish the fact, what causes what. It is a misconception that a correlational study involves two quantitative variables. However, the reality is two variables are measured, but neither is changed. This is true independent of whether the variables are quantitative or categorical.
Types of correlational research
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 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. 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 research
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.
Data collection in correlational research
The distinctive feature of correlational research is that the researcher can’t manipulate either of the variable involved. It doesn’t matter how or where the variables are measured. A researcher could observe participants in a closed environment or a public setting.
Researchers use two data collection methods to collect information in correlational research.
Naturalistic observation is a way of data collection in which people’s behavior is observed in their natural environment, in which they typically exist. This method is a type of field research. It could mean a researcher might be observing people in a grocery store, at the cinema, playground, or similar places.
Researchers who are usually involved in this type of data collection make observations as unobtrusively as possible so that the participants involved in the study are not aware that they are being observed else they might deviate from being their natural self.
Ethically this method is acceptable if the participants remain anonymous, and if the study is conducted in a public setting, a place where people would not normally expect complete privacy. As mentioned previously, taking an example of the grocery store where people can be observed while collecting an item from the aisle and putting in the shopping bags. This is ethically acceptable, and that is the reason most researchers choose public settings for recording their observations. This data collection method could be both qualitative or quantitative.
Another approach to correlational data is the use of archival data. Archival information is the data that has been previously collected by doing similar kinds of research. Archival data is usually made available through primary research.
In contrast to naturalistic observation, the information collected through archived data can be quite straightforward. For example, counting the number of people named Richard in the various states of America based on social security records is quite straightforward.