One way is to first find the interquartile range which we call IQR. Now multiply this by 1.5 and add it to the upper quartile and subtract it from the lower one. Any point beyond these values is an outlier.
An outlier.
An outlier
No. The data set will remain the data set: they are the observations that are recorded.
There cannot be an outlier in a dataset that comprises only one number!
The mean is changed.
there is no outlier because there isn't a data set to go along with it. so theres no outlier
If a data set has an outlier, you would normally deal with it by omitting it from the average of the other values.
An outlier.
Yes there can be more then one outlier
Yes, any data point outside thestandard deviation its an outlier
An outlier
No. The data set will remain the data set: they are the observations that are recorded.
Outlier
There cannot be an outlier in a dataset that comprises only one number!
The mean is changed.
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