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Have you ever seen statistics used to prove a point or make a headline stand out and thought that something was not right? Perhaps a recent study had been conducted on the long-term effects of drinking coffee and you read two different articles about it. One article claimed that drinking coffee provides physical and mental health benefits, but the other was titled, “Top 5 Reasons to Stop Drinking Coffee.” How could two opposing interpretations come from the same study? In order to have a more accurate understanding, you might read the study for yourself. In doing so, you might find that while some negative health effects were reported, such as sleep loss or anxiety, these findings only applied to a small portion of people. Additionally, perhaps the study also mentions that some of the beneficial aspects of coffee drinking were found, but that further studies would need to be conducted in order for the results to be conclusive. Returning to the two articles, did they mention these disclaimers? Whether they did or not, by having a better understanding of how statistics are used to support a hypothesis, you can better prepare yourself to filter the relevancy and accuracy of information that is presented to you.