One might reasonably ask why we bother with correlations at all if causal relationships are what researchers really are seeking to address?
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Correlation does not equal causation! (Huck, 2012; Statistics of Doom, 2016; Lumen, n.d.). This rule is clearly understood, but correlational research is quite useful. First, a brief review of what correlation is. Correlation shows a relationship between two or more variables. As one variable changes, the other variable will change as well. ((Huck, 2012; Statistics of Doom, 2016; Lumen, n.d.).
An example of this was working in performance improvement and measuring waiting time and patient satisfaction. The assumption that patients were happier when the waiting time was shorter was commonly accepted. While these two variables were related, other variables could have been responsible for the satisfaction of the patients. , such as the reception the patients received when they first came in, the engagement of the provider they saw, and the comfort of the waiting area to name a few. But because there was a relationship between waiting and satisfaction, both variables were measured continuously and always; shorter waiting showed a positive relationship with patient satisfaction.
Correlational research is useful to look at the relationship between the variables. This type of research is also crucial in providing quantifiable data (Goss-Sampson, 2019; Statistics of Doom, 2016). The correlation coefficient determines the strength of the relationship between both variables. Scientists use this information to make predictions. For example, when waiting time is longer than 20 minutes, patients are less satisfied. Scientists can also study each variable independently to gain more insight. Correlation research is also useful in making hypotheses. As a previous science teacher, I taught the If…Then scientific method for inquiry. For example, if a slice of bread is left in a moist plastic bag for 3 days, then mold will grow. This hypothesis is based on the knowledge that moisture and heat are excellent mediums for bacterial growth.
Lumen (n.d.) provides an interactive website to test one’s understanding of the correlational relationship. This site offered further clarification of the concept of correlation. This topic is essential to my research as I look at the factors affecting the decision of high school students to attend college. It will be important that I focus on correlations and not mistake them for causal factors.
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