Difference between revisions of "Outlier index - DatLab"

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Outlier index - DatLab

Description

An outlier index (OI) is defined for evaluation of skewness in relation to normal distribution. The OI is derived from Pearson’s coefficient of skewness #2:

Pearson’s coefficient of skewness = 3 · (average-median)/SD

The OI introduces the absolute value of the arithmetic mean, x = ABS(average + median)/2, for normalization:

OI = (average-median)/(x + SD)

OI = (average-median)/[ABS(average+median)/2 + SD]

At the limit of a zero value of x, 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.

Abbreviation: OI

Communicated by Gnaiger E (2016-10-03) updated 2021-06-07

The outlier index in DatLab

In DatLab analysis, the OI is more specific than Pearson’s coefficient of skewness 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 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.

Outlier

» Outlier

» Pearson’s coefficient of skewness, Doane_2011_J Statistics Education: Measuring skewness: a forgotten statistic?

MitoPedia O2k and high-resolution respirometry: DatLab, Oroboros QM

@@ Line 1: / Line 1: @@
 {{MitoPedia
 |abbr=''OI''
-|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,
+|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] #2:
-: ''OI'' = (Average-Median)/(''x'' + SD)
+: Pearson’s coefficient of skewness = 3 · (average-median)/SD
-: ''OI'' = (Average-Median)/[ABS(Average+Median)/2 + SD]
+The ''OI'' introduces the absolute value of the arithmetic mean, ''x'' = ABS(average + median)/2, for normalization:
-By comparison,
+: ''OI'' = (average-median)/(''x'' + SD)
-: Pearson’s coefficient of skewness #2 = 3 x (Average-Median)/SD
+: ''OI'' = (average-median)/[ABS(average+median)/2 + SD]
-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.
+At the limit of a zero value of ''x'', 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''.
 }}
-  Communicated by [[Gnaiger Erich]] () updated 2021-06-07
+  Communicated by [[Gnaiger E]] (2016-10-03) updated 2021-06-07
-{{MitoPedia concepts}}
+== The outlier index in DatLab ==
-{{MitoPedia methods}}
+:::: In DatLab analysis, the ''OI'' is more specific than Pearson’s coefficient of skewness 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.
+== 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?]
 {{MitoPedia O2k and high-resolution respirometry
 |mitopedia O2k and high-resolution respirometry=DatLab, Oroboros QM
 }}
-{{MitoPedia topics}}
-Communicated by [[Gnaiger E]] 2016-10-03; updated 2016-10-22.
-== 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?]