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How could graphics and/or statistics be used to misrepresent data? Where have you seen this done?

In the medial society, graphics and statistics are frequently used to prove (or disprove) theories related to illness and medications. However, the data may be misinterpreted based on an individual’s biased opinion if they are not willing to completely investigate all sides of an argument. This is most common when an individual has a personal, or monetary, interest in a cause. One thing that can easily cause misrepresentation in data is the difference between association and causation—although “variables may be affected by a knowledge of another, does not mean that one variable causes another”(Armitage, Berry, & Matthews, 2008). Another way that data may be misrepresented is in the sample population used—whether they need to meet a specific criteria or random selection without background knowledge. The use of biased studies can often be seen in competitive markets, such as with pharmaceuticals. As many medications are available for the same purpose, they need to find a way to stand out. One way is through use of commercials, as they explain the benefits of the medications, you can often see in very small print information that says results are not typical, or results cannot be guaranteed.
Armitage, P., Berry, G, & Matthews, S. ( 2008, April). Statistical methods in medical research. John Wiley & Sons. Retrieved from ProQuest database

What are the characteristics of a population for which a mean/median/mode would be appropriate? Inappropriate
The appropriate use of mean, median and mode to determine an average is based on the information gathered. “The mean is the arithmetic average, the median is the point representing the 50th percentile in a distribution, and the mode is the most common score” (Nursing Research, 2011).

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