Perhaps the most frequently misunderstood concept in statistics is the difference between correlation and causation. Many thinkincorrectlythat correlationimplies causation. For example, while it may be true that there is a correlation between drinking orange juice and having a reduced risk of a heart attack, this does not necessarily mean that drinking orange juice is the reason (the "cause") for not having a heart attack. Your assignment for this module is to review ONE of the articles below and answer the following questions:

Option #1: Association between coffee consumption and longevity

https://www.cnbc.com/2017/07/11/coffee-drinking-could-lead-to-longer-life-studies-say.html

Option #2: Association between dark chocolate consumption and depression

https://www.fox2detroit.com/news/eating-dark-chocolate-could-reduce-risk-of-depression-study-suggests

Option #3: Association between fitness and mental health

https://www.medicalnewstoday.com/articles/large-study-finds-clear-association-between-fitness-and-mental-health#Is-it-causation

1. Does the author exaggerate the correlation and imply a causal relationship? Provide evidence from the article in 1-2 sentences to support your conclusion.

2. Does the author acknowledge the complexity of the correlation by discussing other variables that could impact the association? These are known as confounding variables. Again, provide evidence from the article in 1-2 sentences to support your answer.

3. Does the author address the limitations of the research, provide an explanation that causation should not be implied, or suggest the need for further research? Again, be sure to use specific examples from the article in 1-2 sentences to support your response.

4. Good statistical journalism often identifies a correlation, includes an explanation that causation is not implied, addresses other variables that can complicate the association, stresses limitations of the current study and the need for ongoing research, and links to the referenced studies.Bad statistical journalism often exaggerates the correlation by implying a causal relationship, misrepresents the results from formal studies, ignores confounding variables and the complexity of the research, and uses clickbait tactics to entice readers.

In summary, do you feel the article is an example of good statistical journalism or bad statistical journalism? Or is the article a mixture of good and bad statistical journalism? Clearly state your position and support with answers from above as well as any other information that you feel is important.

5. Thoughtfully respond to at least 1 post made by another classmate. Feel free to agree with or politely disagree with your classmate's stance, and provide 1-2 sentences to support your thinking.