Who
it messes up the mean and sometimes the median. * * * * * An outlier cannot mess up the median.
The outlier is capable of affecting mean median mode and range it affects mean because the average has changed if affects median because you have to cross out 1 more letter it doesn't affect mode it does affect range because an outlier is a number that i far away from the other numbers * * * * * It does not affect the median.
An* outlier is a number that is much, much greater or much, much less than all/most of the other points. Basically the one that messes up the average, so usually outliers are counted out when finding the mean of a set.
The mean may be a good measure but not if the data distribution is very skewed.
Depends on whether the outlier was too small or too large. If the outlier was too small, the mean without the outlier would be larger. Conversely, if the outlier was too large, the mean without the outlier would be smaller.
It will go down; with outlier, mean is 42 without outlier, mean is 32.5
The mean is changed.
That would be outlier.
An outlier will pull the mean and median towards itself. The extent to which the mean is affected will depend on the number of observations as well as the magnitude of the outlier. The median will change by a half-step.
An outlier is a number that is very high or very low from the others. For example: 10, 15, 20, 5, 25, 25, 20, 50. Its mean would be 21.25, because the 50 is the numbers' outlier.
Calculate the mean, median, and range with the outlier, and then again without the outlier. Then find the difference. Mode will be unaffected by an outlier.
The outlier skews the mean towards it.
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.
An outlier pulls the mean towards it. It does not affect the median and only affects the mode if the mode is itself the outlier.
The mean is affected the most by an outlier.
The outlier is the value that is really far off, for example say you had playing times of songs and most songs were 2 - 4 minutes, but one was 17 minutes, then this would be your outlier. I Hope this helps!