Difference between revisions of "Outlier index - DatLab"

Revision as of 12:02, 3 October 2016

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(median + average)/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, (median-average)/Y. The definition of the outlier index is,

OI = (median-average)/(Y + SD) = (median-average)/[ABS(median+average)/2 + 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 shows indicates the likely occurrence of outliers in the data sequence.

Abbreviation: OI

MitoPedia concepts: "MitoFit Quality Control System" is not in the list (MiP concept, Respiratory state, Respiratory control ratio, SUIT concept, SUIT protocol, SUIT A, SUIT B, SUIT C, SUIT state, Recommended, ...) of allowed values for the "MitoPedia concept" property. MitoFit Quality Control System"MitoFit Quality Control System" is not in the list (Enzyme, Medium, Inhibitor, Substrate and metabolite, Uncoupler, Sample preparation, Permeabilization agent, EAGLE, MitoGlobal Organizations, MitoGlobal Centres, ...) of allowed values for the "MitoPedia topic" property.

MitoPedia O2k and high-resolution respirometry: DatLab

Communicated by Gnaiger E 2016-10-03

Outlier

» Outlier

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

@@ Line 1: / Line 1: @@
 {{MitoPedia
 |abbr=''OI''
-|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 a data series recorded with the O2k. At the limit of a zero value, ''Y'' = ABS(median + average)/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, (median-average)/''Y''. The definition of the outlier index is,
+|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(median + average)/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, (median-average)/''Y''. The definition of the outlier index is,
-''OI'' = (median-average)/(''Y'' + SD)
+''OI'' = (median-average)/(''Y'' + SD) = (median-average)/[ABS(median+average)/2 + 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 [[Marks in DatLab |mark]], the Mark window shows indicates the likely occurrence of outliers in the data sequence.
@@ Line 10: / Line 10: @@
 |mitopedia concept=MitoFit Quality Control System
 }}
-{{MitoPedia methods}}
 {{MitoPedia O2k and high-resolution respirometry
 |mitopedia O2k and high-resolution respirometry=DatLab
 }}
-{{MitoPedia topics}}
+ Communicated by [[Gnaiger E]] 2016-10-03
 == 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?]