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# What are examples of misuse of statistics?

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According to an article from the Wharton School at the University of Pennsylvania, one way statistics are misused is when businesses infer false information from data gained during the course of their business, creating errors that cost time and money. Errors like this arise when an entity performs statistical research but fails to address all the components involved in the subject they are researching.

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Credit: NYC Media Lab CC-BY-SA 2.0

The misuse of statistics can be accidental or purposeful. Those with malicious intent sometimes misuse statistics in order to mislead their audience about a subject, a tactic that creates vast social issues and misunderstandings that last for years.

Misusing statistics is a broader problem than being a tool for the malicious. Scientists and other individuals that rely heavily on analysis and research often find themselves fooled by misused statistics. This creates errors in their experiments or other works, and leads to problems both minor and major.

Statistics are sometimes cherry picked for positive results, creating a false image of the final product. A survey that creates biased opinions about a given subject produces negative results. Other times, if negative results are treated as inconclusive, unless specific reasons are given then the statistics are skewed to seem positive.

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## Related Questions

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The box-and-whisker plot is a technique in statistics that graphically shows the distribution of a set of data involving the minimum and maximum values, as well as the first, second and third quartiles. The plot is typically drawn using a number line.

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The type of math scientists use to analyze data is called statistics. It enables researchers to learn from numbers by measuring, controlling and communicating degrees of certainty and uncertainty, as explained by the American Statistical Association.

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Parametric statistics makes it easier to analyze and describe data with central tendencies and data transformations, according to University of Leicester. The use of parametric statistics versus nonparametric statistics depends on the type of data.