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| {{MitoPedia
| | #REDIRECT [[Outlier-skewness index]] |
| |abbr=''OI''
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| |description=An '''outlier index''' (''OI'') is defined for evaluation of skewness in relation to normal distribution. The ''OI'' is derived from [http://www.statisticshowto.com/pearsons-coefficient-of-skewness/ Pearson’s coefficient of skewness], introducing the absolute value of (Average+Median)/2 for normalization. At the limit of a zero value of ''x'' = ABS(Average + Median)/2, the ''OI'' equals Pearson’s coefficient of skewness #2 (without the multiplication factor of 3). At high ''x'' with small standard deviation (SD), the ''OI'' is effectively the difference between the Average and the Median normalized for ''x'', (Average-Median)/''x''. The definition of the outlier index is,
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| : ''OI'' = (Average-Median)/(''x'' + 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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| In DatLab analysis, the ''OI'' is more specific for targeting outliers in data series recorded with the O2k. 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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| }}
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| Communicated by [[Gnaiger Erich]] () updated 2021-06-07
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| {{MitoPedia concepts}}
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| {{MitoPedia methods}}
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| {{MitoPedia O2k and high-resolution respirometry
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| |mitopedia O2k and high-resolution respirometry=DatLab, Oroboros QM
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| }}
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| {{MitoPedia topics}}
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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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