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 can increase or decrease the mean and median It usually doesn't affect the mode
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.
The median is least affected by an extreme outlier. Mean and standard deviation ARE affected by extreme outliers.
The mean is "pushed" in the direction of the outlier. The standard deviation increases.
it messes up the mean and sometimes the median. * * * * * An outlier cannot mess up the median.
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.
Outlier: an observation that is very different from the rest of the data.How does this affect the data: outliers affect data because it means that your calculations might be off which makes it a possibility that more than the outlier is off.
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 outlier skews the mean towards it.
An outlier can increase or decrease the mean and median It usually doesn't affect the mode
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.
That would be outlier.
The outlier could affect the mean by making it drastically larger or smaller.
It will go down; with outlier, mean is 42 without outlier, mean is 32.5
No. The data set will remain the data set: they are the observations that are recorded.
The mean. Or the mode.