Definitions for outlierˈaʊtˌlaɪ ər

This page provides all possible meanings and translations of the word outlier

Princeton's WordNet

  1. outlier(noun)

    a person who lives away from his place of work

  2. outlier(noun)

    an extreme deviation from the mean

GCIDE

  1. Outlier(n.)

    (Statistics) A datum that lies significantly beyond the main cluster of data points on a graph or diagram; -- suggestive of an error in measurement.

Wiktionary

  1. outlier(Noun)

    A person or thing away from others or outside its proper place.

  2. outlier(Noun)

    A part of a formation separated from the rest of the formation by erosion.

  3. outlier(Noun)

    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.

Freebase

  1. Outlier

    In statistics, an outlier is an observation that is numerically distant from the rest of the data. Grubbs defined an outlier as: An outlying observation, or outlier, is one that appears to deviate markedly from other members of the sample in which it occurs. Outliers can occur by chance in any distribution, but they are often indicative either of measurement error or that the population has a heavy-tailed distribution. In the former case one wishes to discard them or use statistics that are robust to outliers, while in the latter case they indicate that the distribution has high kurtosis and that one should be very cautious in using tools or intuitions that assume a normal distribution. A frequent cause of outliers is a mixture of two distributions, which may be two distinct sub-populations, or may indicate 'correct trial' versus 'measurement error'; this is modeled by a mixture model. In most larger samplings of data, some data points will be further away from the sample mean than what is deemed reasonable. This can be due to incidental systematic error or flaws in the theory that generated an assumed family of probability distributions, or it may be that some observations are far from the center of the data. Outlier points can therefore indicate faulty data, erroneous procedures, or areas where a certain theory might not be valid. However, in large samples, a small number of outliers is to be expected.


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