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A Graphical Method of Removing Outlier Values from Analytical Data.
NTIS: PB 197 023 :10 pages
Often a collection of analytical data, which should reasonably be expected to follow the normal distribution, contains too many extreme values, which the experimenter is inclined to eliminate according to some arbitrary procedure. The stepwise computer procedure described for this purpose is similar to many other truncation procedures; however, because truncation of a basically normal distribution causes a downward bias in the estimated variance, this procedure provides a graphical method to compensate for the bias.
IH; Report of Investigations
NTIS Accession No.
NTIS: PB 197 023
Page last reviewed: September 2, 2020
Content source: National Institute for Occupational Safety and Health Education and Information Division