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Why is it important for researchers to eliminate significant outliers from their data before running a statistical test? Woul
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An outlier is a value that is very different from the other data in data set. They skew study results. they increase error variance and limit the power of statistical tests. In non random distribution, they can decrease normality, increasing the risk of making both Type I and Type II errors. Third, they can seriously bias or influence predictions that may be of utmost  interest.

the impact of outlier in small dataset will be more as compared to large dataset as a single extreme value in small dataset will cause inflation of standard deviation to a great extent. Whereas in large dataset., impact of outlier is not that strong.

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