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Data Science & Analytics vocabulary · Exploratory Analysis

Outlier

Meaning in data science & analytics, with examples

/ˈaʊtlaɪər/nounCore term

In data science & analytics, outlier means: A value that is very far from most of the other values in a dataset, for example one order of 50,000 dollars among orders of around 40 dollars.

In Turkish: aykırı değer, uç değer

How it is used

You detect, investigate, remove or cap outliers. A careful analyst first asks whether an outlier is an error or a real and important case. Common in EDA, data cleaning and when explaining surprising averages.

Example sentences

  1. The average order value jumped because of a few outliers from wholesale customers.

  2. Don't just delete the outliers; check whether they're data entry errors first.

Common collocations

  • detect outliers
  • remove outliers
  • extreme outlier
  • outlier detection
  • anomalyA data point or pattern that clearly differs from what is expected, such as a sudden spike in sign-ups or a day with no orders at all.
  • meanThe value you get by adding all the numbers in a group and dividing the total by how many numbers there are; the usual meaning of 'average'.
  • medianThe middle value when all the numbers in a group are sorted from smallest to largest; half the values are below it and half are above it.
  • distributionThe way the values of a variable are spread out, showing which values are common, which are rare and how far apart they are; often viewed as a histogram.

This word in other fields

The same English word can have a different meaning in another field:

More terms: Exploratory Analysis

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