JOURNAL ENTRY

Correlation and Causation Student’s Name Institution Course Instructor Date of Submission Correlation and Causation It is important to learn the relationship between correlation and causation. This relationship is important in social research and critical thinking. The fact that the correlations can reveal the trends of the variables does not mean that one variable will cause the other to vary. This is a big difference in research and life in general in understanding patterns and decision-making. In this journal, I will define correlation and causation, give my own examples, and comment on how this understanding has assisted me in critically evaluating any relationship between variables. Correlation is a statistical association between two variables since one variable's variation is connected to another variable's (Mclod, 2023). Causation, in turn, presupposes that the change in one variable causes a change in another (Qualtrics, n.d.). Among the key principles is that correlation does not necessarily imply causation; i.e., because two things happen together, it does not mean that one causes the other. As an illustration, my podcast listening habits are more likely to increase as I face more work. Although the two variables are moving in the same direction, the workload does not make me listen to more podcasts; instead, the workload and the stress are affected by a third factor- stress. This is an example of how a spurious relationship may seem important but be motivated by another variable (Kenton, 2024). Two examples of non-causal correlation have been observed in my personal life. To begin with, the amount of coffee I consume and the number of e-mails I get daily increase in tandem. Although this is a positi...