The following module provides an overview of correlational research and when it is used.
Define correlational research
Describe basic types of correlations
Describe examples of when correlational research methods are utilized
The following video link offers an excellent introduction to the topic of correlational research: Correlation Research. Correlational research is used to explore the relationships or links between variables. It does not describe the nature of the relationship as in descriptive research and it cannot be used to determine causation as experimental research. Rather, it measures the extent to which two variables are related. The purpose of the research it to determine which variables are interacting and what type of interaction is occurring. This allows the researcher to make predictions based on the relationship found. For example, if a change in variable A consistently resulted in a change to variable B, a correlational relationship could be described.
In correlational research, the researcher does not have control over or manipulate either variable. The role of the researcher is to gather the data and determine if there is a pattern that indicates a correlational relationship between the variables. A researcher may decide to look for a correlation between age and the number of tickets received for traffic violations. The role of researcher is to analyze and interpret the data, but neither variable is controlled by the researcher. Correlational studies can take in a natural setting, a laboratory setting, or by simply collecting data available through a variety of means.
There are 3 basic types of correlations. If an increase in variable A occurs and results in an increase in variable B, there is a positive correlation. A positive correlation occurs whenever the change in the variables is occurring in the same direction. For example, an increase in the number of hours that students study could result in an increase in test scores or lower ACT scores may indicate poorer performance in college. These are both examples of positive correlations because the variables are moving in the same direction. A negative correlation occurs when one variable increases and the other variable decreases. An example would be the relationship between increasing exercise and reducing the number of doctor visits for colds and common illnesses. Finally, there may be zero correlation when there is no identifiable pattern for determining a relationship. For example, there may be no relationship found between the number of cups of coffee drank per day and intelligence. These correlational relationships and the statistical analyses of correlational data will be discussed in more detail in the next modules in this series.
In summary, it may be helpful to distinguish correlational research from some of the other common types of research that have been covered in other modules. The following video further explains correlational research by comparing and contrasting it with descriptive and experimental research studies.
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