outliners

statistical outliers can significantly skew the results of your analysis.

we need to identify and remove outliers from the dataset before proceeding.

the box plot clearly shows several outliers in the distribution.

outliers in medical data can sometimes indicate rare conditions.

some researchers argue that outliers should not be automatically excluded.

the presence of outliers affected the mean significantly.

our algorithm detected three outliers in the customer purchase records.

extreme outliers require careful investigation before removal.

financial analysts must distinguish between genuine outliers and data errors.

removing outliers without investigation can lead to misleading conclusions.

the z-score method is commonly used to detect statistical outliers.

these outliers represent the most interesting cases in our study.