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 is a number completely different from the rest in a set of data.For example, in the set:13, 17, 22, 15, 19, 11, 342, 14342 is the outlier.
i don't know but it's one ov my vocab that i have to turn in:)
It's possible. An outlier is a number that affects the the mean of a group of numbers greatly. For example the mean in this set of numbers (2, 4, 1, 5) is 3, but if I add the number 93 the new answer is 21.
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.
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.
Outliers pull the mean in the direction of the outlier.
An outlier is a number completely different from the rest in a set of data.For example, in the set:13, 17, 22, 15, 19, 11, 342, 14342 is the outlier.
the outlier is 23 and it made it decrease
i don't know but it's one ov my vocab that i have to turn in:)
On the standard deviation. It has no effect on the IQR.
It's possible. An outlier is a number that affects the the mean of a group of numbers greatly. For example the mean in this set of numbers (2, 4, 1, 5) is 3, but if I add the number 93 the new answer is 21.
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.
The one that does not belong
if the oulier is REALLY high, the mean gets higher if the outlier is REALLY low, the mean gets lower
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.
a number that is unlike the other numbers. example: if you had the numbers 22, 24, 25, 105 and 20 the outlier would be 105 because it is so far away from the other numbers