No. The data set will remain the data set: they are the observations that are recorded.
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.
That would be outlier.
An outlier is a value that is way too small or way too large compared to other observations. There is no formal definition of what "way too" is.
Range is the largest minus the smallest value in the data set. An outlier is a value that is far away from the majority of the data.
Not necessarily.
An outlier will have a huge affect on the range as the range is the largest value minus the smallest value.
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.
That would be outlier.
Outliers pull the mean in the direction of the outlier.
An outlier is a value that is way too small or way too large compared to other observations. There is no formal definition of what "way too" is.
There would be a difference to the median. The old number wouldn't be the median but the mode wouldn't change. If the outlier is a high value, it will cause the mean value to shift to the higher side, while a low valued outlier will drop the mean value to a lower number.
An outlier (mathematics/statistics), or radical value (sociology).
outlier
Range is the largest minus the smallest value in the data set. An outlier is a value that is far away from the majority of the data.
Range subtracts the lowest value from the value in your data set. If you have an outlier, meaning a number either obviously outside the data, your range will be incorrect because one of the values will not represent the average pattern of the data. For example: if your data values include 1,2,3,4,and 17, 17 would be the outlier. The range would be 16 which is not truly representative of the rest of the data.
Not necessarily.
Outlier