Correlation: Difference between revisions
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#<div class="definition"><div class="short_definition">In general, a mutual relationship between [[variables]] or other entities.</div><br/> <div class="paragraph">In [[statistical]] terminology, it is a form of [[statistical dependence]].</div><br/> </div> | #<div class="definition"><div class="short_definition">In general, a mutual relationship between [[variables]] or other entities.</div><br/> <div class="paragraph">In [[statistical]] terminology, it is a form of [[statistical dependence]].</div><br/> </div> | ||
#<div class="definition"><div class="short_definition">When used without further qualification, the [[statistical]] term correlation usually refers to simple, [[linear correlation]] between two variables ''x'', ''y'' and is measured by the [[product-moment]] coefficient of correlation ρ or its [[sample]] estimate ''r'' defined as follows, where the respective [[population]] mean values of ''x'' and ''y'' are denoted by ξ and ζ, the respective [[standard deviations]] by σ(''x'') and σ('' y''), and where ''E'' is the [[expected value]]: <div class="display-formula"><blockquote>[[File:ams2001glos-Ce41.gif|link=|center|ams2001glos-Ce41]]</blockquote></div> <div class="display-formula"><blockquote>[[File:ams2001glos-Ce42.gif|link=|center|ams2001glos-Ce42]]</blockquote></div></div><br/><div class="paragraph">The product moment ''E''[(''x'' | #<div class="definition"><div class="short_definition">When used without further qualification, the [[statistical]] term correlation usually refers to simple, [[linear correlation]] between two variables ''x'', ''y'' and is measured by the [[product-moment]] coefficient of correlation ρ or its [[sample]] estimate ''r'' defined as follows, where the respective [[population]] mean values of ''x'' and ''y'' are denoted by ξ and ζ, the respective [[standard deviations]] by σ(''x'') and σ('' y''), and where ''E'' is the [[expected value]]: <div class="display-formula"><blockquote>[[File:ams2001glos-Ce41.gif|link=|center|ams2001glos-Ce41]]</blockquote></div> <div class="display-formula"><blockquote>[[File:ams2001glos-Ce42.gif|link=|center|ams2001glos-Ce42]]</blockquote></div></div><br/><div class="paragraph">The product moment ''E''[(''x'' - ξ) (''y'' - ζ)] is usually called the [[covariance]] of ''x'' and ''y''. In connection with correlation, the word "simple" is used in contradistinction to other qualifiers such as "multiple" or "partial." The word "linear" refers to a [[linear]] relationship between the two variables, or more precisely, to a linear approximation of the [[regression function]] of either [[variate]] with respect to the other. <br/>''See'' [[autocorrelation]], [[multiple correlation]], [[partial correlation]].</div><br/> </div> | ||
#<div class="definition"><div class="short_definition"><br/>''See'' [[correlation coefficient]].</div><br/> </div> | #<div class="definition"><div class="short_definition"><br/>''See'' [[correlation coefficient]].</div><br/> </div> | ||
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Latest revision as of 13:59, 20 February 2012
correlation
- In general, a mutual relationship between variables or other entities.
In statistical terminology, it is a form of statistical dependence.
- When used without further qualification, the statistical term correlation usually refers to simple, linear correlation between two variables x, y and is measured by the product-moment coefficient of correlation ρ or its sample estimate r defined as follows, where the respective population mean values of x and y are denoted by ξ and ζ, the respective standard deviations by σ(x) and σ( y), and where E is the expected value:The product moment E[(x - ξ) (y - ζ)] is usually called the covariance of x and y. In connection with correlation, the word "simple" is used in contradistinction to other qualifiers such as "multiple" or "partial." The word "linear" refers to a linear relationship between the two variables, or more precisely, to a linear approximation of the regression function of either variate with respect to the other.
See autocorrelation, multiple correlation, partial correlation.