Classmates Response:

Hi Class

From this article I read about the misuse of statistics, specifically correlation vs causation. The article also delves into overgeneralization and biased samples. I have also discerned that statistics can be misleading when numbers are cherry-picked to support a specific viewpoint, ignoring broader trends or context. An example from last week would be the biased questions and cases of correlation not equaling causation.

An example of skewed statistics would be the "red wine is healthy" myth. This conception that red wine is healthy for you was born of poor statistical interpretation. Researchers monitored the health of 500,000 people, and those who responded with at least having 1 alcoholic per day were less likely to perish from any cause. This is clearly another correlation vs causation misuse of statistics, as those who could afford to red wine everyday typically had better means to healthcare. Additionally, the initial research population consisted of ex-drinkers who no longer could take another sip least they risk liver failure.

References:

Lumen Learning. (n.d.). The use and misuse of statistics | Public speaking. https://courses.lumenlearning.com/wm-publicspeaking/chapter/the-use-and-misuse-of-statistics/

Callahan, A. (Feb, 2024). How Red Wine Lost its Health Halo | The New York Times. https://www.nytimes.com/2024/02/17/well/eat/red-wine-heart-health.html

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