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"outlier rejection" vs "Outlier Elimination"

Both 'outlier rejection' and 'outlier elimination' are correct phrases used in the context of data analysis and statistics. They refer to the process of identifying and removing outliers from a dataset. The choice between the two may depend on the specific context or preference of the speaker, as they convey a similar meaning.

Last Updated: April 01, 2024

outlier rejection

This phrase is correct and commonly used in the context of data analysis and statistics.

This phrase refers to the process of identifying and excluding outliers from a dataset in statistical analysis.

Examples:

  • The data set underwent outlier rejection before the final analysis.

Alternatives:

  • outlier removal
  • outlier exclusion
  • outlier detection

Outlier Elimination

This phrase is correct and commonly used in the context of data analysis and statistics.

This phrase also refers to the process of identifying and removing outliers from a dataset in statistical analysis.

Examples:

  • Outlier elimination is a crucial step in ensuring the accuracy of statistical models.

Alternatives:

  • outlier removal
  • outlier exclusion
  • outlier detection

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