outlier

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outlier

 [out´li-er]
an observation so distant from the central mass of the data that it noticeably influences results and must be carefully checked to ensure it is not an error.

out·li·er

(owt'lē-ĕr),
An observation that differs so widely from all others in a set as to justify the conclusion that a gross error has occurred or that it comes from a different population.

outlier

/out·li·er/ (out´li-er) an observation so distant from the central mass of the data that it noticeably influences results.

outlier

1 (in managed care) a case in which costs exceed the allowable amount for the specific diagnosis or treatment. The outlier amount is typically specified in advance in the contract between the provider and payer.
2 (in research) an observation that differs from all others, suggesting that a gross error has occurred in sampling, measurement, or analysis.

outlier

Any value outside of an expected range.

outlier

Managed care A Pt who falls outside of the norm–ie, who has an extremely long length of hospital stay or has incurred extraordinarily high costs. See Extreme outlier, High mortality outlier.

out·li·er

(owt'lī-ĕr)
1. Deviant values or figures that are obviously from a different population than those from the rest of the sample.
2. Additions to an estimated cost of delivered services when exceeding a fixed loss threshold.

outlier

an extremely high or low value lying beyond the range of the bulk of the data.
References in periodicals archive ?
If you are an outlier, you should ask yourself why, and consider peer review and other appropriate changes.
By this way the privacy of the dataset is maintained using l-diversity and information loss is reduced using KNN classifier by assigning the outliers to its nearest clusters.
As noted above, research has examined performance of the heavy tailed method with outliers in the context of latent variable and single level models, and found that they work well under many conditions in these contexts.
In addition, since the established models are generally given in a compact manner, it is possible to detect outliers without storage of the original data set.
2008); thus, the size and location of any outliers is difficult to evaluate, and the gain matrix has a more complex structure.
This method will prove useful for empirical analyses where infeasible outliers appear above the frontier from a different distribution than the inefficiency.
For each of the simulation scenarios, we removed outliers using 2 approaches; a standard approach of one round of removing outliers >3 SDs from the mean difference, and the IOR approach.
Moreover, the QQ plot was employed for the quantiles of the corrected Pearson residuals against the quantiles of the estimated shifted gamma distribution to detect outliers.
The majority of extreme outliers for each year and standardization method belonged to the "Local Employment" indicator.