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Deceptive Statistics

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Statistics expressed as numbers are evidence. People always use statistics as evidence and to support their reasoning. These statistics makes evidence appear precise and scientific. They are regarded to as hard evidence. However, statistics can lie and do often lie. They necessarily do not always prove what they appear to prove. This paper explains some deceptive or questionable statistics.
A survey done on golf claimed that one way to make money quick is by becoming a professional golfer. It further stated that an average professional golfer earned $999,876.65 in 2015 alone. In any professional sport, they are few individuals who win extremely high amounts. These individuals are the pros and tend to win almost every tournament. The huge winnings have a great impact on the mean. They increase it dramatically. However, they do not have a big effect on the mode and the median of the professional golfers’ earnings. The author may have used the mean intentionally as the huge winnings would skew the mean up and make professional golfing lucrative for everybody. This is not the case anyway. This is a case of confusing averages.
Sometimes statistics may be incomplete or intentionally omitted to achieve the author’s intent. Take for instance this study that concluded that skydiving is safer than driving. It found that in a particular month, in Los Angeles 4 people died of skydiving and 51 of car accidents. These statistics are not enough to prove that skydiving is safer than driving. How many people skydive and how many people drive.

Wait! Deceptive Statistics paper is just an example!

The study should have come up with percentages instead.
A study done at a shopping mall concluded that 50% of Americans cheat on their spouses. Out the 102-people interviewed 50 admitted to having once cheated on someone they were ‘seeing.’ The study claims to prove the rate of cheating among spouses whereas it conducted research on lovers but not necessarily spouses. This is a case of proving one thing and claiming another.
The above examples are just but a few of how statistics can be deceptive.

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