Correlational research is a type of scientific investigation in which a researcher looks at the relationships between variables but does not vary, manipulate, or control them. It can be a useful research method for evaluating the direction and strength of the relationship between two or more different variables.
When examining how variables are related to one another, researchers may find that the relationship is positive or negative. Or they may also find that there is no relationship at all.
How Does Correlational Research Work?
In correlational research, the researcher measures the values of the variables of interest and calculates a correlation coefficient, which quantifies the strength and direction of the relationship between the variables.
The correlation coefficient ranges from -1.0 to +1.0, where -1.0 represents a perfect negative correlation, 0 represents no correlation, and +1.0 represents a perfect positive correlation.
A negative correlation indicates that as the value of one variable increases, the value of the other variable decreases, while a positive correlation indicates that as the value of one variable increases, the value of the other variable also increases. A zero correlation indicates that there is no relationship between the variables.
|The variables both increase together
|The more you walk on a treadmill, the more calories you burn.
|The variables decrease together
|The less you study, the lower your grades will be.
|No relationship exists between the variables
|How much you walk on a treadmill is not associated with grades on exams.
Correlational Research vs. Experimental Research
Correlational research differs from experimental research in that it does not involve manipulating variables. Instead, it focuses on analyzing the relationship between two or more variables.
In other words, correlational research seeks to determine whether there is a relationship between two variables and, if so, the nature of that relationship.
Experimental research, on the other hand, involves manipulating one or more variables to determine the effect on another variable. Because of this manipulation and control of variables, experimental research allows for causal conclusions to be drawn, while correlational research does not.
Both types of research are important in understanding the world around us, but they serve different purposes and are used in different situations.
|Utilized to assess the strength and direction of the relationship between variables
|Utilized to look for cause-and-effect relationships between variables
|Involves measuring but not manipulating variables
|Involves manipulating an independent variable and measuring the effect on the dependent variable
|Results may be influenced by other variables that the researcher cannot control
|Researchers are better able to control extraneous variables that might impact results
Types of Correlational Research
There are three main types of correlational studies:
Cohort Correlational Study
This type of study involves following a cohort of participants over a period of time. This type of research can be useful for understanding how certain events might influence outcomes.
For example, researchers might study how exposure to a traumatic natural disaster influences the mental health of a group of people over time.
By examining the data collected from these individuals, researchers can determine whether there is a correlation between the two variables under investigation. This information can be used to develop strategies for preventing or treating certain conditions or illnesses.
Cross-Sectional Correlational Study
A cross-sectional design is a research method that examines a group of individuals at a single time. This type of study collects information from a diverse group of people, usually from different backgrounds and age groups, to gain insight into a particular phenomenon or issue.
The data collected from this type of study is used to analyze relationships between variables and identify patterns and trends within the group.
Cross-sectional studies can help identify potential risk factors for certain conditions or illnesses, and can also be used to evaluate the prevalence of certain behaviors, attitudes, or beliefs within a population.
Case-Control Correlational Study
A case-control correlational study is a type of research design that investigates the relationship between exposure and health outcomes. In this study, researchers identify a group of individuals with the health outcome of interest (cases) and another group of individuals without the health outcome (controls).
The researchers then compare the exposure history of the cases and controls to determine whether the exposure and health outcome correlate.
This type of study design is often used in epidemiology and can provide valuable information about potential risk factors for a particular disease or condition.
When to Use Correlational Research
There are a number of situations where researchers might opt to use a correlational study instead of some other research design.
Correlational research can be used to investigate a wide range of psychological phenomena, including the relationship between personality traits and academic performance, the association between sleep duration and mental health, and the correlation between parental involvement and child outcomes.
To Generate Hypotheses
Correlational research can also be used to generate hypotheses for further research by identifying variables that are associated with each other.
To Investigate Variables Without Manipulating Them
Researchers should use correlational research when they want to investigate the relationship between two variables without manipulating them. This type of research is useful when the researcher cannot or should not manipulate one of the variables or when it is impossible to conduct an experiment due to ethical or practical concerns.
To Identify Patterns
Correlational research allows researchers to identify patterns and relationships between variables, which can inform future research and help to develop theories. However, it is important to note that correlational research does not prove that one variable causes changes in the other.
While correlational research has its limitations, it is still a valuable tool for researchers in many fields, including psychology, sociology, and education.
How to Collect Data in Correlational Research
Researchers can collect data for correlational research in a few different ways. To conduct correlational research, data can be collected using the following:
- Surveys: One method is through surveys, where participants are asked to self-report their behaviors or attitudes. This approach allows researchers to gather large amounts of data quickly and affordably.
- Naturalistic observation: Another method is through observation, where researchers observe and record behaviors in a natural or controlled setting. This method allows researchers to learn more about the behavior in question and better generalize the results to real-world settings.
- Archival, retrospective data: Additionally, researchers can collect data from archival sources, such as medical, school records, official records, or past polls.
The key is to collect data from a large and representative sample to measure the relationship between two variables accurately.
Pros and Cons of Correlational Research
There are some advantages of using correlational research, but there are also some downsides to consider.
- One of the strengths of correlational research is its ability to identify patterns and relationships between variables that may be difficult or unethical to manipulate in an experimental study.
- Correlational research can also be used to examine variables that are not under the control of the researcher, such as age, gender, or socioeconomic status.
- Correlational research can be used to make predictions about future behavior or outcomes, which can be valuable in a variety of fields.
- Correlational research can be conducted quickly and inexpensively, making it a practical option for researchers with limited resources.
- Correlational research is limited by its inability to establish causality between variables. Correlation does not imply causation, and it is possible that a third variable may be influencing both variables of interest, creating a spurious correlation. Therefore, it is important for researchers to use multiple methods of data collection and to be cautious when interpreting correlational findings.
- Correlational research relies heavily on self-reported data, which can be biased or inaccurate.
- Correlational research is limited in its ability to generalize findings to larger populations, as it only measures the relationship between two variables in a specific sample.
Frequently Asked Questions About Correlational Research
What are the main problems with correlational research?
Some of the main problems that can occur in correlational research include selection bias, confounding variables. and misclassification.
- Selecting participants based on their exposure to an event means that the sample might be biased since the selection was not randomized.
- Correlational studies may also be impacted by extraneous factors that researchers cannot control.
- Finally, there may be problems with how accurately data is recorded and classified, which can be particularly problematic in retrospective studies.
What are the variables in a correlational study?
In a correlational study, variables refer to any measurable factors being examined for their potential relationship or association with each other. These variables can be continuous (meaning they can take on a range of values) or categorical (meaning they fall into distinct categories or groups).
For example, in a study examining the correlation between exercise and mental health, the independent variable would be exercise frequency (measured in times per week), while the dependent variable would be mental health (measured using a standardized questionnaire).
What is the goal of correlational research?
The goal of correlational research is to examine the relationship between two or more variables. It involves analyzing data to determine if there is a statistically significant connection between the variables being studied.
Correlational research is useful for identifying patterns and making predictions but cannot establish causation. Instead, it helps researchers to better understand the nature of the relationship between variables and to generate hypotheses for further investigation.
How do you identify correlational research?
To identify correlational research, look for studies that measure two or more variables and analyze their relationship using statistical techniques. The results of correlational studies are typically presented in the form of correlation coefficients or scatterplots, which visually represent the degree of association between the variables being studied.
Correlational research can be useful for identifying potential causal relationships between variables but cannot establish causation on its own.
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Kendra Cherry, MS.Ed., is an author, educator, and founder of Explore Psychology, an online psychology resource. She is a health writer and editor specializing in psychology, mental health, and wellness. She also writes for Verywell Mind and is the author of the Everything Psychology book (Adams Media).
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