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.
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.
The median is the middle of average of the middle two values from the ordered set of observations. If the extreme values are genuine then they will have no effect on the median. If they are incorrectly measured or recorded data then they may affect the position of the middle of the ordered set of data. However, since there can only be a small number of outliers, their effect on the median will be small.
Both the mean and median represent the center of a distribution. Calculating the mean is easier, but may be more affected by outliers or extreme values. The median is more robust.
extreme values don't affect the mode
in general,mean is more stable than median but in the case of extreme values it is better to consider median a stable measure than 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.
The median is the middle of average of the middle two values from the ordered set of observations. If the extreme values are genuine then they will have no effect on the median. If they are incorrectly measured or recorded data then they may affect the position of the middle of the ordered set of data. However, since there can only be a small number of outliers, their effect on the median will be small.
median
Because it is easily influenced by extreme values (i.e. it is not unbiased).
when there are extreme values in the data
The mean is used to measure the average of a set of values, especially when the data is normally distributed. The median is used to find the middle value of a dataset when there are extreme values or outliers present, as it is less affected by extreme values.
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.
You would use the median if the data were very skewed, with extreme values.
An outlier can significantly impact the median by pulling it towards the extreme value of the outlier, especially when the dataset is small. This can distort the central tendency measure that the median represents and provide a misleading representation of the typical value in the dataset.
Both the mean and median represent the center of a distribution. Calculating the mean is easier, but may be more affected by outliers or extreme values. The median is more robust.
extreme values don't affect the mode
in general,mean is more stable than median but in the case of extreme values it is better to consider median a stable measure than mean.