Correlation and causation are always heard like two peas in a pod. Sometimes I hear them used as correspondents and sometimes not. Correlations between variables show us that there is a pattern in the data: that the variables we have tend to move together. However, correlations alone don’t show us whether or not the data are moving together because one variable causes the other(JMP 2021). Even if there is a correlation between two variables, we cannot conclude that one variable causes a change in the other. This relationship could be coincidental, or a third factor may be causing both variables to change(Khan Academy 2021). an example of this would be when doing research on psychiatric medications. How do we know that the medications are what is affecting the imbalance of our thoughts and our feelings? There are also some other factors that could contribute to the side effects like not having enough nutritious vitamins as well as feeling stressed out. I always think about this when I used to work in a behavioral hospital. Then I would try to figure out ways to help the patients non-medicinally like doing yoga or going out on the patio or creating fun activities for the patients and their peers to release Seratonin. It helped alongside the medication which was a great outcome for their care.
Resources
Khan Academy. (n.d.). Correlation and causation | Lesson (article). Khan Academy. Retrieved October 3, 2021, from https://www.khanacademy.org/test-prep/praxis-math/praxis-math-lessons/gtp–praxis-math–lessons–statistics-and-probability/a/gtp–praxis-math–article–correlation-and-causation–lesson.
Correlation vs causation. JMP. (n.d.). Retrieved October 3, 2021, from https://www.jmp.com/en_us/statistics-knowledge-portal/what-is-correlation/correlation-vs-causation.html.
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