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.
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 answer depends on the nature of the outlier. Removing a very small outlier will increase the mean while removing a large outlier will reduce the mean.
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.
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.
It will go down; with outlier, mean is 42 without outlier, mean is 32.5
Yes, it will. An outlier is a data point that lies outside the normal range of data. This means that if it is factored in the mean will move in the direction the outlier is, really high if the outlier was high, and really low if the outlier was low.
The mean is "pushed" in the direction of the outlier. The standard deviation increases.
The outlier could affect the mean by making it drastically larger or smaller.
That would be outlier.