Correlational Research Design
Correlational Research Design is a type of nonexperimental research design that is used to examine the relationship between two or more variables.
In a Correlational Study, the researcher does not manipulate or control the independent variable, but instead observes the relationship between the independent and dependent variables. This is used in the Quantitative Research Method.
Correlational Research
Correlational Research is a type of research that investigates the relationships between variables. These variables can be anything that can be measured, such as attitudes, behaviors, or even thoughts. Correlational research is used to find out if there is a relationship between two or more variables and how strong that relationship is. This type of research can be used to predict future behavior or to understand why certain behaviors happen.
Correlational Research Types
There are three types of Correlational Research Design:
- Positive Correlational
- Negative Correlational
- No correlation
Positive Correlational
Positive correlational research means that as one variable increases, the other variable also increases.
Example:
If there is a positive correlation between study habits and grades, it means that students who study more tend to get better grades.
Negative Correlational
Negative correlational research means that as one variable increases, the other variable decreases.
Example
If there is a negative correlation between smoking and lifespan, it means that people who smoke tend to live shorter lives than those who don’t smoke.
No correlation
It indicates that there is no relationship between the two variables.
Correlational Research Data Collection Methods
Correlational Data Can be gatherd in the following ways:
- Surveys
- Observational Data
- Existing Data Sets
Surveys
Surveys can be administered in person, over the phone, or online. They typically ask questions about people’s opinions, beliefs, or behaviors.
Observational Data
This involves observing people in their natural environment and taking note of their behavior.
Existing Data Sets
This could involve looking at data from previous studies or from administrative records.
Correlational Research Data Analysis Methods
Some common methods include:
- Pearson’s correlation coefficient
- Spearman’s rank correlation coefficient
- Kendall’s tau
Pearson’s correlation coefficient
This measures the strength of the linear relationship between two variables.
Spearman’s rank correlation coefficient
This measures the strength of the relationship between two variables when there is no linear relationship.
Kendall’s tau
This measures the strength of the relationship between two variables when there is no linear or monotonic relationship.
When to use Correlational Research
There are a few things to consider before using correlational research.
- It is important to make sure that the two variables are actually related.
- It is important to ensure that there is not another variable that is causing the relationship between the two variables.
- It is important to note that correlational research cannot prove that one variable causes another; it can only identify associations between them.
Also see Qualitative Research
Correlational Research Example
- One example of correlational research would be a study looking at the relationship between people’s level of income and their level of happiness. The researcher in this study would simply observe and measure both income and happiness levels, without manipulating either variable.
- Another example of correlational research would be a study looking at the relationship between how much television people watch and how obese they are.
Advantages of Correlational Research
There are many advantages to conducting correlational research.
- This type of research is relatively easy and inexpensive to conduct.
- Correlational research can provide a great deal of information about the relationships between different variables. This information can be used to develop hypotheses about the causes of certain phenomena.
- It can help researchers identify factors that may be associated with particular outcomes.
Also see Mixed Methods Research
Disadvantages of Correlational Research
Some disadvantage of this type of research method is the following.
- When two variables are correlated, it does not mean that one variable caused the other. There could be a third, unknown variable causing the correlation. This is known as a confounding variable.
- Correlational research is that it cannot prove that one variable causes another. Only a randomized controlled trial can establish causation.
- It can also be used to identify relationships between variables, but it cannot determine the strength of those relationships.
