Whether you are a beginner or an experienced researcher, chances are you’ve heard something about correlational research. It’s time that you learn more about this type of study more in-depth, since you will be using it a lot.
- What is correlation?
- When to use it?
- How is it different from experimental studies?
- What data collection method will work?
Grab your pen and get ready to jot down some notes as our paper writing service is going to cover all questions you may have about this type of study. Let’s get down to business!
What Is Correlational Research: Definition
A correlational research is a preliminary type of study used to explore the connection between two variables. In this type of research, you won’t interfere with the variables. Instead of manipulating or adjusting them, researchers focus more on observation.
Correlational study is a perfect option if you want to figure out if there is any link between variables. You will conduct it in 2 cases:
- When you want to test a theory about non-causal connection. For example, you may want to know whether drinking hot water boosts the immune system. In this case, you expect that vitamins, healthy lifestyle and regular exercise are those factors that have a real positive impact. However, this doesn’t mean that drinking hot water isn’t associated with the immune system. So measuring this relationship will be really useful.
- When you want to investigate a causal link. You want to study whether using aerosol products leads to ozone depletion. You don’t have enough expenses for conducting complex research. Besides, you can’t control how often people use aerosols. In this case, you will opt for a correlational study.
Correlational Study: Purpose
Correlational research is most useful for purposes of observation and prediction. Researcher's goal is to observe and measure variables to determine if any relationship exists. In case there is some association, researchers assess how strong it is. As an initial type of research, this method allows you to test and write the hypotheses. Correlational study doesn’t require much time and is rather cheap.
Correlational Research Design
Correlational research designs are often used in psychology, epidemiology, medicine and nursing. They show the strength of correlation that exists between the variables within a population. For this reason, these studies are also known as ecological studies.
Correlational research design methods are characterized by such traits:
- Non-experimental method. No manipulation or exposure to extra conditions takes place. Researchers only examine how variables act in their natural environment without any interference.
- Fluctuating patterns. Association is never the same and can change due to various factors.
- Quantitative research. These studies require quantitative research methods. Researchers mostly run a statistical analysis and work with numbers to get results.
- Association-oriented study. Correlational study is aimed at finding an association between 2 or more phenomena or events. This has nothing to do with causal relationships between dependent and independent variables.
Correlational Research Questions
Correlational research questions usually focus on how one variable related to another one. If there is some connection, you will observe how strong it is. Let’s look at several examples.
Examples of correlational research questions
Is there any relationship between the regular use of social media and eating habits?
There is a positive relationship between the frequent use of social media and excessive eating.
There is no relationship between the time spent on social media and eating habits.
What effect does social distancing have on depression?
There is a strong association between the time people are isolated and the level of depression.
There is no association between isolation and depression.
Correlational Research Types
Depending on the direction and strength of association, there are 3 types of correlational research:
- Positive correlation If one variable increases, the other one will grow accordingly. If there is any reduction, both variables will decrease.
- Negative correlation All changes happen in the reverse direction. If one variable increases, the other one should decrease and vice versa.
- Zero correlation No association between 2 factors or events can be found.
Correlational Research: Data Collection Methods
There are 3 main methods applied to collect data in correlational research:
- Surveys and polls
- Naturalistic observation
- Secondary or archival data.
It’s essential that you select the right study method. Otherwise, it won’t be possible to achieve accurate results and answer the research question correctly. Let’s have a closer look at each of these methods to make sure that you make the right choice.
Surveys in Correlational Study
Survey is an easy way to collect data about a population in a correlational study. Depending on the nature of the question, you can choose different survey variations. Questionnaires, polls and interviews are the three most popular formats used in a survey research study. To conduct an effective study, you should first identify the population and choose whether you want to run a survey online, via email or in person.
Naturalistic Observation: Correlational Research
Naturalistic observation is another data collection approach in correlational research methodology. This method allows us to observe behavioral patterns in a natural setting. Scientists often document, describe or categorize data to get a clear picture about a group of people. During naturalistic observations, you may work with both qualitative and quantitative research information. Nevertheless, to measure the strength of association, you should analyze numeric data.
Members of a population shouldn’t know that they are being studied. Thus, you should blend in a target group as naturally as possible. Otherwise, participants may behave in a different way which may cause a statistical error.
Correlational Study: Archival Data
Sometimes, you may access ready-made data that suits your study. Archival data is a quick correlational research method that allows to obtain necessary details from the similar studies that have already been conducted. You won’t deal with data collection techniques, since most of numbers will be served on a silver platter. All you will be left to do is analyze them and draw a conclusion. Unfortunately, not all records are accurate, so you should rely only on credible sources.
Pros and Cons of Correlational Research
Choosing what study to run can be difficult. But in this article, we are going to take an in-depth look at advantages and disadvantages of correlational research. This should help you decide whether this type of study is the best fit for you. Without any ado, let’s dive deep right in.
Advantages of Correlational Research
Obviously, one of the many advantages of correlational research is that it can be conducted when an experiment can’t be the case. Sometimes, it may be unethical to run an experimental study or you may have limited resources. This is exactly when ecological study can come in handy.
This type of study also has several benefits that have an irreplaceable value:
- Works well as a preliminary study
- Allows examining complex connection between multiple variables
- Helps you study natural behavior
- Can be generalized to other settings.
If you decide to run an archival study or conduct a survey, you will be able to save much time and expenses.
Disadvantages of Correlational Research
There are several limitations of correlational research you should keep in mind while deciding on the main methodology. Here are the advantages one should consider:
- No causal relationships can be identified
- No chance to manipulate extraneous variables
- Biased results caused by unnatural behavior
- Naturalistic studies require quite a lot of time.
As you can see, these types of studies aren’t end-all, be-all. They may indicate a direction for further research. Still, correlational studies don’t show a cause-and-effect relationship which is probably the biggest disadvantage.
Difference Between Correlational and Experimental Research
Now that you’ve come this far, let’s discuss correlational vs experimental research design. Both studies involve quantitative data. But the main difference lies in the aim of research. Correlational studies are used to identify an association which is measured with a coefficient, while an experiment is aimed at determining a causal relationship.
Due to a different purpose, the studies also have different approaches to control over variables. In the first case, scientists can’t control or otherwise manipulate the variables in question. Meanwhile, experiments allow you to control variables without limit.
There is a causation vs correlation blog on our website. Find out their differences as it will be useful for your research.
Example of Correlational Research
Above, we have offered several correlational research examples. Let’s have a closer look at how things work using a more detailed example.
You want to determine if there is any connection between the time employees work in one company and their performance. An experiment will be rather time-consuming. For this reason, you can offer a questionnaire to collect data and assess an association. After running a survey, you will be able to confirm or disprove your hypothesis.
Correlational Study: Final Thoughts
That’s pretty much everything you should know about correlational study. The key takeaway is that this type of study is used to measure the connection between 2 or more variables. It’s a good choice if you have no chance to run an experiment. However, in this case you won’t be able to control for extraneous variables. So you should consider your options carefully before conducting your own research.
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Frequently Asked Questions About Correlational Study
1. What is a correlation?
Correlation is a connection that shows to which extent two or more variables are associated. It doesn’t show a causal link and only helps to identify a direction (positive, negative or zero) or the strength of association.
2. How many variables are in a correlation?
There can be many different variables in a correlation which makes this type of study very useful for exploring complex relationships. However, most scientists use this research to measure the association between only 2 variables.
3. What is a correlation coefficient?
Correlation coefficient (ρ) is a statistical measure that indicates the extent to which two variables are related. Association can be strong, moderate or weak. There are different types of p coefficients: positive, negative and zero.
4. What is a correlational study?
Correlational study is a type of statistical research that involves examining two variables in order to determine association between them. It’s a non-experimental type of study, meaning that researchers can’t change independent variables or control extraneous variables.