Statistical outlier definition

Statistical outlier means an individual data point that has a value far from those of the other data points in a set and that has been determined through statistical analysis to have derived from a different population than the other data points.
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Examples of Statistical outlier in a sentence

  • Statistical outlier analyses were then performed with SanitasTM using the 1989 EPA outlier test.

  • The TCFE22) thermodynamic database, MOB223) mobility database, and experimental pa- rameters, i.e., cooling rate and secondary arm spacing, were used in DICTRA simulations.

  • Statistical outlier detection found four outliers; three participants due to their significantly greater abilities to play the game, and one participant due to their high cybersickness scores.

  • Statistical outlier deletion, based on the 99th percentile, was then applied to these measures with the aim to discard anomalous values.

  • Statistical outlier criteria (study group-wise detection): volume outliers (amygdala and hippocampal [sub-]regions and brain hemispheres separately) and bilateral symmetry outliers (amygdala and hippocampal [sub-]regions separately, based on lateralization index LI=(lh-rh)/(lh+rh)).

  • Common Article 3 of the Geneva Conventions prohibits “violence to life and person” including cruel treatment, torture, and “outrages upon personal dignity.” Geneva Convention Relative to the Treatment of Prisoners of War art.

  • Statistical outlier analyses were then performed SanitasTM using the 1989 EPA outlier test.

  • Statistical outlier detec- tion methods are divided into two categories: parametric methods and non- parametric methods.

  • Flags – Number of flags are used to highlight specific results (not applicable to all participants) Aberrant: Results reported that do not meet the evaluation criteria or do not agree with the reference result. Statistical outlier: A numerical result that is outside the upper or lower statistical limits as defined by Tukey’s filter.

  • Statistical outlier finding [39] and anomaly detection [48] use statistical analysis and interactive techniques to direct end-user programmers’ attention to potentially problematic areas during automation tasks.

Related to Statistical outlier

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