None - as long as the ouliers move away from the median - which they should.
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The mean is better than the median when there are outliers.
Outliers are observations that are unusually large or unusually small. There is no universally agreed definition but values smaller than Q1 - 1.5*IQR or larger than Q3 + 1.5IQR are normally considered outliers. Q1 and Q3 are the lower and upper quartiles and Q3-Q1 is the inter quartile range, IQR. Outliers distort the mean but cannot affect the median. If it distorts the median, then most of the data are rubbish and the data set should be examined thoroughly. Outliers will distort measures of dispersion, and higher moments, such as the variance, standard deviation, skewness, kurtosis etc but again, will not affect the IQR except in very extreme conditions.
The median and mode cannot be outliers. For small samples a mode could be an outlier.
It shows the minimum, lower quartile, median, upper quartile and maximum of a set of observations. It may show outliers separately.It shows the minimum, lower quartile, median, upper quartile and maximum of a set of observations. It may show outliers separately.It shows the minimum, lower quartile, median, upper quartile and maximum of a set of observations. It may show outliers separately.It shows the minimum, lower quartile, median, upper quartile and maximum of a set of observations. It may show outliers separately.
an outliers can affect the symmetry of the data because u can still move around it