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By definition, an outlier will not have the same value as other data points in the dataset. So, the correct question is "What is the effect of an outlier on a dataset's mean." The answer is that the outlier moves the mean away from the value of the other 49 identical values. If the outlier is the "high tail" the mean is moved to a higher value. If the outlier is a "low tail" the mean is moved to a lower value.

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โˆ™ 2009-04-10 14:57:49
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Q: If an outlier is included with a sample of 50 values all of which are the same what is the effect of the outlier on the mean?
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Related questions

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An outlier is a value in a data set that is numerically distant from the other values. This definition is not rigorous, as I have not clearly identified a test to determine a value which is "numerically distant." However, in many situations, the definition is sufficient to identify values outside of an observable trend or grouping. The importance of the outlier depends on the statistics being calculated. If we are calculating the median price of a home, and we include a one huge mansion, the median will only be slightly effected. However, if we are calculating the cost of the most expensive houses, say in the top 10% percentile, the outlier will have a significant effect. See related link on outliers.

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