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Yes.
Yes.
Yes.
Yes.
Wiki User
∙ 11y ago
Wiki User
∙ 11y agoYes.
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Between Mean Median and Mode which are affected most by an outlier?
The mean is affected the most by an outlier.
Which measure is most affected by an outlier?
mean
If you take off the outlier does it make the mean change?
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.
If an outlier is included with a sample of 50 values all of which are the same what is the effect of the outlier on the mean?
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.
Would a mean be smaller or larger if you leave out an outlier?
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.
Between Mean Median and Mode which are affected most by an outlier?
The mean is affected the most by an outlier.
How are the mean and standard deviation affected by an outlier?
The mean is "pushed" in the direction of the outlier. The standard deviation increases.
Which measure is most affected by an outlier?
mean
If you take off the outlier does it make the mean change?
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.
Which of the following is least affected if an extreme high outlier is added to your data mean median or standard deviation or ALL?
The median is least affected by an extreme outlier. Mean and standard deviation ARE affected by extreme outliers.
How does the outlier affect the mean of the data?
An outlier does affect the mean of the data. How it's affected depends on how many data points there are, how far from the data the outlier is, whether it is greater than the mean (increases mean) or less than the mean (decreases the mean).
How would the outlier affect the mean and median of the data?
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.
If an outlier is included with a sample of 50 values all of which are the same what is the effect of the outlier on the mean?
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.
How does the outlier affect the mean?
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.
What would happen if a outlier was removed from the mean?
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.
What is an outliers effect on the mean?
if the oulier is REALLY high, the mean gets higher if the outlier is REALLY low, the mean gets lower
Would a mean be smaller or larger if you leave out an outlier?
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.
