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| {{MitoPedia
| | #REDIRECT [[Outlier-skewness index]] |
| |abbr=''OI''
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| |description=An '''outlier index''' (''OI'') is defined for DatLab analysis, derived from [http://www.statisticshowto.com/pearsons-coefficient-of-skewness/ 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,
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| : ''OI'' = (Average-Median)/(''Y'' + SD)
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| : ''OI'' = (Average-Median)/[ABS(Average+Median)/2 + SD]
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| By comparison,
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| : Pearson’s coefficient of skewness #2 = 3 x (Average-Median)/SD
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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.
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| {{MitoPedia concepts
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| |mitopedia concept=MitoFit Quality Control System
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| }}
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| {{MitoPedia O2k and high-resolution respirometry
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| |mitopedia O2k and high-resolution respirometry=DatLab
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| }}
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| Communicated by [[Gnaiger E]] 2016-10-03; updated 2016-10-22.
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| == Outlier ==
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| ::::» [[Outlier]]
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| ::::» [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?]
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