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 ?
In addition, the main effect of percent of outlying observations was also statistically significantly related to estimation bias for [[beta].
1] by method and percent of outlying observations appear in the bottom panel of Table 5.
133), as was the main effect of percent of outlying observations ([F.
00] by percent of outlying observations and estimation method, averaged across the other variables.
1] by the percentage of outlying observations and method of estimation for level-2 outliers are presented in the bottom panel of Table 10.
This statistic is very sensitive to outlying observations tending to exaggerate the variance of prediction errors of model choices in which the prediction error is larger than the others (which is typical in land price studies).