Correlational research
Correlational research is a scientific method used to explore the relationships between two or more variables, which may include statistics, behaviors, or other observable factors. This approach helps researchers determine how variables interact, whether they increase or decrease simultaneously, or if they appear unrelated. While correlational research can provide valuable insights into various scientific questions—such as the effects of sitting for prolonged periods on heart disease—it does not establish causation, meaning it cannot definitively prove that one variable causes changes in another.
Researchers typically employ surveys or observational methods to gather data for correlational studies. Surveys may involve asking participants about their behaviors or experiences, while observational studies involve monitoring variables without interference. The outcomes of these studies can be represented mathematically through a correlational coefficient, ranging from -1 to +1, which indicates the strength and direction of the relationship between variables. A positive coefficient suggests a direct relationship, a negative one indicates an inverse relationship, and a coefficient near zero implies no significant correlation. This type of research plays a crucial role in advancing our understanding of complex interactions in various fields, including health, psychology, and social sciences.
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Correlational research
Correlational research is a method by which people study how two or more variables are related. These variables may be statistics, behaviors, or other measurable or observable factors. Scientists use correlational research to determine whether variables increase or decrease at the same time; one variable increases while the other decreases; or the variables seem to have no relationship. The effects of this research can help to answer a variety of scientific questions; however, such research cannot prove with certainty whether one variable causes another variable. Correlational research may be performed in different ways but is mainly accomplished through surveys or observation.
Overview
Many scientific questions relate to relationships between variables. Do plants grow faster when they are in sunlight? (Here, the relationship is between plant growth and sunlight.) Are people more prone to criminal behavior in big cities than in small towns? (The relationship is between people in big cities and people in small towns.) Examining the possible relationships between variables can be of great value to science and society. For that reason, scientists turn to correlational research to determine whether variables are related, and, if so, how.
A scientist may be faced with a claim that when people sit for long periods, they are in greater danger of developing heart disease. The relationship here is between sitting for long periods and developing heart disease. In many other cases, scientists can conduct experiments to test their ideas. However, it would be neither practical nor ethical to ask experiment subjects to sit for long periods to see if their health deteriorates. Scientists therefore turn to correlational research to verify or disprove this claim. They will need to study cases in which people sat for long periods and determine whether these people were more likely than the regular population to develop heart disease.
The two main methods of conducting correlational research are through surveys and observations. Surveys involve asking people questions related to the research topic. They may be conducted in person, through mailings, on the internet, or by phone. Scientists may also use naturalistic observation. That involves directly observing a variable without interfering with it. In the case of the previously mentioned study, the scientist would likely conduct a survey of people who sit for long periods and ask them whether they have experienced any heart problems.
The results of correlational research can be converted into a mathematical figure called a correlational coefficient. This is a number that ranges from –1 to +1. A positive correlation means that the variables seem to be closely related. If many people who sit too much have heart disease, the correlation will likely be positive. A negative correlation signifies that when one variable increases, the other decreases. (For example, if people increase their exercise level, their level of heart disease will likely decrease.) A correlation at or near zero suggests that the variables are probably not related at all. These results can be plotted on graphs and used to make scientific predictions.
Bibliography
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Johnson, Burke, and Larry Christensen. Educational Research: Quantitative, Qualitative, and Mixed Approaches. 8th ed., SAGE Publications, 2024.
McLeod, Saul. "Correlation in Psychology: Meaning, Types, Examples, & Coefficient." SimplyPsychology, 31 July 2023, www.simplypsychology.org/correlation.html. Accessed 6 Sept. 2024.
Mertens, Donna M. Research and Evaluation in Education and Psychology. 6th ed., SAGE Publications, 2024.
Siegle, Del. "Introduction to Correlation Research." University of Connecticut, Neag School of Education, 11 Oct. 2015, researchbasics.education.uconn.edu/correlation/. Accessed 6 Sept. 2024.