Определение outliers в Английский Язык Английский Язык словарь
(Data Analysis) Data values in a time series which are significantly different from the series trend and/or other data values such that their inclusion may jeopardize the model's ability to fit the data If such sample data values cannot be explained by other, external factors, then they should probably be omitted from the model estimation process altogether
Technically, outliers are data items that did not (or are thought not to have) come from the assumed population of data -- for example, a non-numeric when you are expecting only numeric values A more casual usage refers to data items that fall outside the boundaries that enclose most other data items in the data set
unexpected responses usually produced by agents and objects far from one another in location along the variable
In all histogram options an analysis is taken up to see the outliers This applies to the DATA/VIEW EDIT option where the columns are looked at via the Alt-C keystroke Secondly the ANALYSIS/RESIDUALS HISTOGRAM option allows you in the same way to detect the interesting outliers The fit that has a high breakpoint with respect to outliers is the ANALYSIS/LEAST MEDIAN SQUARES option
Patients with unique conditions or illnesses that cannot be classified under the standard groups
Medicare patients whose illnesses are unique and whose conditions may not be classifiable under one of the diagnostic related groups
Those patients with a specific admitting diagnosis that either have a shorter or longer length of stay than the usual range for that diagnosis
Data points which do not appear to follow the characteristic distribution of the rest of the data These may reflect genuine properties of the underlying phenomenon (variable), or be due to measurement errors or other anomalies which should not be modeled
In healthcare the term is used in two ways To refer to a hospital patient accommodated in a different ward from that specialising in the relevant medical diagnosis The term may be used in the examination of data where results fall well outside the pattern for the majority of NHS Trusts with similar units
observations that differ markedly from the pattern established by the vast majority
An extreme value that does not fit into the normal range of values for a given variable; for example, in a sample of test scores if most students score between a 75 and a 98, a student with a score of 30 would be an outlier
Cases with extremely long lengths-of-stay (day outliers) or extraordinarily high costs (cost outliers) compared with others classified in the same diagnosis-related group Hospitals receive additional PPS payments for these cases
A value in a statistical sample which does not fit a pattern that describes most other data points; specifically, a value that lies 1.5 IQR beyond the upper or lower quartile
A comparative term describing a patient whose stay in the hospital is unusually long or whose costs for hospital care are unusually high compared to other patients with the same diagnosis or condition The Medicare program uses DRGs as categories to identify outliers Under Medicare, additional payments are made for outliers meeting certain conditions
{i} person or thing that lies outside of or away from; person who lives some distance from his place of work; section of rock separated from the main formation by erosion (Geology)
A patient who varies significantly from other patients in the same DRG (such as a longer or shorter length of stay, death, leaving against medical advice, etc ) Also, a person whose performance varies significantly from established normative standards (e g , a physician whose utilization patterns are notably abnormal)
A patient record with an unusually high or low value, given the DRG There are two ways that a record can become an outlier First, the facility may identify a record as an outlier when submitting its patient data Second, severity analysis software may determine that the reported value is significantly greater or less than the norm, given the DRG
A node whose exclusion from its containing peer group would significantly improve the accuracy and simplicity of the aggregation of the remainder of the peer group topology
departure from an average, usually defined as at least two standard deviations from the mean; in managed care systems these are frequently consumers for whom expenditures are more than the average, lengths of stay in inpatient care is greater than is typical for persons with a similar condition or consumers who are given exceptional treatment subject to peer review and organization review
a hospital admission requiring either substantially more expense or a much longer length of stay than average Under DRG reimbursement, outliers are given exceptional treatment (subject to peer review and organization review)
A standing stone set apart from the main formation of a stone circle, sometimes in an astronomically significant direction (for example midsummer's sunrise) Sometimes they mark the "entrance" to a stone circle Examples are the Heel Stone at Stonehenge and the King Stone at the Rollright Stones
One who does not fall within the norm; term typically used in utilization review A provider who uses either too many or too few services (for example, anyone whose utilization differs 2 standard deviations from the mean on a bell curve is termed an "outlier ")
(Ticaret) An observed value so far removed from the normal distribution that it may be considered an abnormality or one-time event, and is often not included in future calculations based on that set of data
A statistical term referring to isolated data values that fall well outside the range of values measured for nearly all other data points in a given set of observations Various conventions exist for deciding when a given data value should be considered an outlier (e g if it falls 4 or more standard deviations above or below the mean for that set of observations) Outliers are sometimes indicative of data-entry errors or other types of artifacts, and therefore need to be scrutinized carefully before attempting to perform statistical analyses with a given set of data
An individual who does not fall within the norm This term often refers to providers who use significantly more or less resources than their peers For example, any provider whose utilization differs two standard deviations from the mean on a bell curve may be deemed as outlier The term "outlier" can also refer to enrollees who consume significantly more or less resources than most patients with their diagnoses
Generally, an unusual case In the DRG context, an admitted patient who stays much longer (day outlier) or who costs much more (cost outlier) than the average for the DRG to which the episode belongs (Eagar, K & Hindle, D 1994, The Australian Casemix Dictionary, National Casemix Education Series No 9, Department of Human Services & Health, Canberra)
A data value that does not follow the characteristic distribution of a given set of data A data value that falls far above or far below the middle of a distribution
A measurement (from a radar detection system) that has a (set of) state value(s) outside the three-times-standard-deviation interval around the mean value(s) or outside a user specified limit
An outlier is an observation that is many SD's from the mean It is sometimes tempting to discard outliers, but this is imprudent unless the cause of the outlier can be identified, and the outlier is determined to be spurious Otherwise, discarding outliers can cause one to underestimate the true variability of the measurement process
an observed value that appears to be discordant from the other observations in a sample One of a set of observations that appears to be discordant from the others The declaration of an outlier is dependent on the significance level of the applied identification test See also Significance level
A data value which is unusual with respect to the group of data in which it is found It may be a single isolated value far away from all the others, or a value which does not follow the general pattern of the rest Most classical statistical techniques tend to be quite sensitive to outliers, so that it is important to be on the alert for them Graphical techniques, particularly residual plots, are very helpful in detecting the presence of outliers Some of the newer Exploratory Data Analysis techniques and nonparametric procedures are much less sensitive to outliers (such procedures are said to be robust)