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when there are extreme values in the data
MEDIANUse the median to describe the middle of a set of data that does have an outlier.Advantages:• Extreme values (outliers) do not affect the median as strongly as they do the mean.• Useful when comparing sets of data.• It is unique - there is only one answer.Disadvantages:• Not as popular as mean.
True. I've included a link which will help you understand why.
The advantage of harmonic mean is that it is used to solve situations in which there are extreme data values to true picture. The disadvantage of it is that it can be time consuming to evaluate the data.
Generally not without further reason. Extreme values are often called outliers. Eliminating unusually high values will lower the standard deviation. You may want to calculate standard deviations with and without the extreme values to identify their impact on calculations. See related link for additional discussion.
extreme values don't affect the mode
No they do not (or at least they have less of a significant impact) and this is the benefit of using the median average over the mean average.
An extreme value will drag the mean value towards it.
mode and mean
When there aren't extreme values (outliers)
weighted mean
when there are extreme values in the data
MEDIANUse the median to describe the middle of a set of data that does have an outlier.Advantages:• Extreme values (outliers) do not affect the median as strongly as they do the mean.• Useful when comparing sets of data.• It is unique - there is only one answer.Disadvantages:• Not as popular as mean.
No, extremely high or low values will not affect the median. Because the median is the middle number of a series of numbers arranged from low to high, extreme values would only serve as the end markers of the values.
Any variation is very sensitive to extreme values!
mean
MEDIANUse the median to describe the middle of a set of data that does have an outlier.Advantages:• Extreme values (outliers) do not affect the median as strongly as they do the mean.• Useful when comparing sets of data.• It is unique - there is only one answer.Disadvantages:• Not as popular as mean.