Learn all about correlational research with definitions of correlational research, examples of correlational research, and methods of correlational research.
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A dietician may want to find out if there is any correlation between vegetarianism and a healthy body. The dietician conducts research on a group of people with different diets (vegan, non-vegetarians, and vegetarians). They then statistically analyzes the result to determine whether the people with a Vegetarian diet are healthier than others.
To conduct such a study what is the best way where the researcher instead of being actively involved passively observes the involved subjects. For such relationship investigation the correlation research comes into play.
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By definition correlational research refers to a type of non-experimental research method that evaluates the relationship between the variables with the help of statistical analysis.
Correlational research design does not study the effects of extraneous variables on the variables under study.
In terms of market research, a correlational study is generally used to study quantitative data and identify whether any patterns, trends, or insights exist between consumer behavior and market variables such as; advertisements, discounts, as well as discounts on products.
Correlational research design is useful for all kinds of quantitative data sets, but it is commonly used within market research. Market researchers find it useful to use correlational design with Customer Effort Score Surveys and their association with sales; Customer Experience (CX) and its relationship with customer loyalty, as well as Net Promoter Score Surveys and its correlation with brand image or management.
These surveys include many relevant questions that make them ideal to study in correlational research design. In market research, correlational methods help in isolating variables and seeing how they interact with each other.
Also read: What is Descriptive Research?
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A correlation coefficient describes the strength & association relationship between variables.
It is a statistical technique for data analysis. Among various correlation coefficients, the most popular is Pearson’s correlation coefficient.
A correlation coefficient ranges from -1 to +1. A correlation coefficient of +1 reveals a perfect positive correlation whereas a correlation coefficient of -1 indicates a perfect negative correlation between two variables. A coefficient of 0 reveals that there is no relationship between the variables under study.
Here’s an example of correlational research:
Consider a hypothetical study on hypertension and marital satisfaction where a researcher is aiming to study the relationship between disease (hypertension) and marital satisfaction. If the researcher finds a negative correlation between these two variables indicating that as marital satisfaction increases, experiences of hypertension decrease.
However, this does not mean that marital dissatisfaction is causing hypertension, it just highlights an association between them. In correlational research design, none of the variables under study are manipulated or changed. They are just measured and the associations between them are observed or examined.
For instance, you want to understand if there is a correlation between how much you earn and spend.
You may carry out correlational research to see if any relationship between the two exists.
If you find out positive correlation it indicates that as the amount of earning increases the spending also increases.
Let’s look at another example of correlational research.
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To understand it better, let’s take a look at some of the crucial characteristics of correlational research which are as follows:
Correlational research is a non-experimental method. It indicates that investigators do not have to use the formal technique to modify factors in agreeing or dispute with such a concept. The investigator just analyzes and examines the relationship among variables, not changing or modifying them in any way.
Correlational study that is solely willing to look backwards at historical information and observe the past. It is used by scientists to assess and identify long term trends among 2 factors. A correlational analysis may reveal an advantageous association between variables, but that link might shift in the upcoming years.
Correlational study results involving 2 factors that are never static and are continually evolving. Based on a variety of causes, two parameters with a negative correlation in the prior may well have a positive correlation connection in the future.
Now that we’ve studied its characteristics, let’s move to understanding the different types of correlation research that exist.
Also read: Sampling Methods
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Typically there are three types of correlational research:
A positive correlation demonstrates that there is a positive relationship between the two variables. In this kind of relation, as one variable increases, the other variable also increases. For example, the number of cars a person owns is positively correlated with their income. More the income, more the number of cars.
A negative correlation indicates that there is a negative relationship between the two variables. In this kind of correlation, as one variable increases, the other variable decreases. For instance, a negative relationship between levels of stress and life satisfaction indicates that as stress levels increase, life satisfaction decreases.
Zero correlation demonstrates that there is no relationship between the the variables. A change in one variable does not cause any changes in the other variable. An example of zero correlation is the relationship between intelligence and height. An increase in height does not lead to any changes in the intelligence of an individual.
In naturalistic observation, the participants of the study are observed in their natural environments. This observation is a kind of field study. You can observe participants in grocery stores, cinemas, playgrounds, schools, etc.
Researchers who use it as a means of data collection observe individuals as unobtrusively as possible. This is because they don’t want the people to be aware of being monitored as it may influence their behavior and they may not be their natural selves.
For instance, if you are observing consumers in a grocery store and the kind of items they usually buy, it is ethically acceptable as customers know that they are subjected to being observed in public spaces. The insights collected in a naturalistic environment can be qualitative or quantitative.
Archival data is another approach 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. There is no scope for the observer effect in archival data.
For instance, assessing the average customer satisfaction with electronic products for a particular brand in America is straightforward.
Also read: Exploratory Research
Correlational research comes with a distinct set of advantages:
Now, let’s explore some of the disadvantages
While there are various advantages, there are a few disadvantages of correlational research such as
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While correlation does not necessarily imply causation, causation does imply correlation. Correlational research is a stepping-stone to the more powerful experimental method and is more useful than it may seem because some of the recently developed complex correlational designs allow for some very limited causal inferences.
Findings from correlational research can be used to determine prevalence and relationships among variables, and to forecast events from current data and knowledge.
When a study identifies and establishes a relationship between two or more naturally occurring variables with one another. Hence, identifying how these two or more variables are related. The stress of teenage peer pressure links with the performance.
The major difference between correlational research method and experimental research is that in correlational research, the researcher looks for a statistical pattern linking 2 naturally-occurring variables while in experimental research, the researcher introduces a catalyst and monitors its effects on the variables.
When a research design is being investigated solely on the basis of its variables without any interference from the researcher manipulation or control. The relationship is focused on the variables of the study. For example weight where the value differs naturally and it can’t be manipulated by the involved researcher.
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