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"outlier rejection" vs "eliminating outlier"

Both phrases are correct and commonly used in the context of data analysis. 'Outlier rejection' is a term often used in statistics to refer to the process of identifying and removing outliers from a dataset. 'Eliminating outlier' is also correct but less commonly used compared to 'outlier rejection'.

Last Updated: April 01, 2024

outlier rejection

This phrase is correct and commonly used in statistics to refer to the process of identifying and removing outliers from a dataset.

This term is used in the context of data analysis, particularly in statistics, to describe the process of identifying and removing outliers from a dataset.

Alternatives:

  • outlier removal
  • outlier detection
  • outlier elimination
  • outlier filtering
  • outlier trimming

eliminating outlier

This phrase is correct but less commonly used compared to 'outlier rejection'. It conveys the same meaning of removing outliers from a dataset.

While less common, 'eliminating outlier' can still be used to describe the process of removing outliers from a dataset, particularly in the context of data analysis.

Alternatives:

  • removing outliers
  • filtering outliers
  • detecting outliers
  • trimming outliers
  • removing anomalies

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