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Grand Canyon University *

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Biology

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May 18, 2024

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docx

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Uploaded by ChefKnowledge7114

Hello professor and class, Correlation and causality are commonly used interchangeably, causing confusion about what each phrase means. However, in the scientific world, these are two very different concepts. Correlation is the study of how two variables vary and interact with one another. Causality is the concept of one thing causing another. Correlation does not imply causality; correlation just indicates the presence of a substantial association between two variables. In contrast, the following description of causation is a significantly more powerful example of correlation: Someone who lifts weights is more likely to enjoy chicken nuggets than someone who does not. This is because lifting weights causes muscles to grow stronger, and the bodybuilder needs protein to help with this process. Additional investigations have shown that protein is necessary for the formation of strong muscles. When a person stops eating chicken nuggets, his muscles stop growing and he loses weight, so he is likely to cease lifting weights. There are many differences between correlation and causality. The distinctions include the following: Correlation constitutes a statistical word, whereas causality is the prediction of a future event using previous events. As an outcome, both concepts are difficult to measure and forecast. Cause and effect cannot be quantified quantitatively or qualitatively, although correlation can. This means that, while correlation can be quantified by employing a numerical framework, causation cannot because there is no numerical structure capable of establishing what caused something to exist in the first place. Understanding Causality and Correlation will help corporate managers build new products by allowing them to understand the impact of multiple factors on product sales. For example, a computer department manager can utilize the correlation coefficient to determine how advertising affects product sales. If there is no link between advertising and sales, then advertising has no impact on sales. Reference Van Hul, M., Le Roy, T., Prifti, E., Dao, M. C., Paquot, A., Zucker, J. D., ... & Cani, P. D. (2020). From correlation to causality: the case of Subdoligranulum. Gut microbes , 12 (1), 1849998 Gelman, A. (2011). Causality and statistical learning.
Herrmann, C. S., Strüber, D., Helfrich, R. F., & Engel, A. K. (2016). EEG oscillations: from correlation to causality. International Journal of Psychophysiology , 103 , 12-21. Saraswati, S., & Sitaraman, R. (2015). Aging and the human gut microbiota—from correlation to causality. Frontiers in microbiology , 5 , 764.
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