Phi coefficient
Type of coefficient
In statistics, the phi coefficient, also known as the mean square contingency coefficient or Yule coefficient of correlation and commonly denoted by φ or rφ, is a measure of association between two binary variables. In machine learning and bioinformatics, it is known as the Matthews correlation coefficient (MCC).
Nº Q4811327 ★
Common · Knowledge
Phi coefficient
Type of coefficient
In statistics, the phi coefficient, also known as the mean square contingency coefficient or Yule coefficient of correlation and commonly denoted by φ or rφ, is a measure of association between two binary variables. In machine learning and bioinformatics, it is known as the Matthews correlation coefficient (MCC).
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From Wikipedia
In statistics, the phi coefficient, also known as the mean square contingency coefficient or Yule coefficient of correlation and commonly denoted by φ or rφ, is a measure of association between two binary variables. In machine learning and bioinformatics, it is known as the Matthews correlation coefficient (MCC). In meteorology and elsewhere, it is referred to as the Doolittle Measure of Association or Doolittle Skill Score. Described by Udny Yule in 1912 and given the name phi by Karl Pearson in the 1930s, it is a special case of the Pearson correlation coefficient.
Text: Wikipédia, CC BY-SA 4.0. ·
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