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Graphics and statistics can be used to misrepresent data when sound methods are not used to reach the stated statistic or conclusion. For example, data that are not necessarily related, but is presented in such a way that the reader or audience draws what seem like an obvious conclusion, when there is really a third or completely different cause. Bad sampling can also result in faulty, misleading statistics.
An example of misleading statistics could be:
"Suppose we want to dramatize how much the price of candy bars has gone up. We might have the following data:
January $ .76
February $ .54
March $ .51
April $ .63
May $ .80
June $ .91
July $ .76
We could correctly say that the price jumped from 51 cents to 91 cents in only three months (March to June), an increase of more than 78%! On the other hand, we can see it didn't change at all from January to July, which we might avoid mentioning if we wanted to impress people with the price increase. Choosing the starting and ending points for data used is an easy way to deliberately manipulate statistics.
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