Difference between revisions of "Outlier index - DatLab"
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The threshold of the absolute value of the ''OI'' is set at 0.05. If ABS(''OI'')>0.05 calculated for the data points within a defined [[Marks - DatLab |Mark]], the Mark window indicates the likely occurrence of outliers in the data sequence. The threshold can be set to a lab-specific or session-specific value different from the default value. | The threshold of the absolute value of the ''OI'' is set at 0.05. If ABS(''OI'')>0.05 calculated for the data points within a defined [[Marks - DatLab |Mark]], the Mark window indicates the likely occurrence of outliers in the data sequence. The threshold can be set to a lab-specific or session-specific value different from the default value. | ||
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{{MitoPedia O2k and high-resolution respirometry | {{MitoPedia O2k and high-resolution respirometry | ||
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Communicated by [[Gnaiger E]] 2016-10-03; updated 2016-10-22. | |||
== Outlier == | == Outlier == | ||
::::» [[Outlier]] | ::::» [[Outlier]] | ||
::::» [http://www.statisticshowto.com/pearsons-coefficient-of-skewness/ Pearson’s coefficient of skewness], [https://ww2.amstat.org/publications/jse/v19n2/doane.pdf Doane_2011_J Statistics Education: Measuring skewness: a forgotten statistic?] | ::::» [http://www.statisticshowto.com/pearsons-coefficient-of-skewness/ Pearson’s coefficient of skewness], [https://ww2.amstat.org/publications/jse/v19n2/doane.pdf Doane_2011_J Statistics Education: Measuring skewness: a forgotten statistic?] | ||
Revision as of 22:31, 5 May 2019
- high-resolution terminology - matching measurements at high-resolution
Outlier index - DatLab
Description
An outlier index (OI) is defined for DatLab analysis, derived from Pearson’s coefficient of skewness, but more specific in targeting outliers in data series recorded with the O2k. At the limit of a zero value, Y = ABS(Average + Median)/2, the OI equals Pearson’s coefficient of skewness #2 (without the multiplication factor of 3). At high Y with small standard deviation (SD), the outlier index is effectively the difference between the Average and the Median normalized for the absolute value, (Average-Median)/Y. The definition of the outlier index is,
- OI = (Average-Median)/(Y + SD)
- OI = (Average-Median)/[ABS(Average+Median)/2 + SD]
By comparison,
- Pearson’s coefficient of skewness #2 = 3 x (Average-Median)/SD
The threshold of the absolute value of the OI is set at 0.05. If ABS(OI)>0.05 calculated for the data points within a defined Mark, the Mark window indicates the likely occurrence of outliers in the data sequence. The threshold can be set to a lab-specific or session-specific value different from the default value.
Abbreviation: OI
MitoPedia O2k and high-resolution respirometry:
DatLab,
Oroboros QM
Communicated by Gnaiger E 2016-10-03; updated 2016-10-22.
