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 &#x003c1; or its [[sample]] estimate ''r'' defined as follows, where the respective [[population]]  mean values of ''x'' and ''y'' are denoted by &#x003be; and &#x003b6;, the respective [[standard deviations]] by  &#x003c3;(''x'') and &#x003c3;('' 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'' &minus; &#x003be;) (''y'' &minus; &#x003b6;)] is usually called the [[covariance]] of ''x'' and ''y''. In  connection with correlation, the word &ldquo;simple&rdquo; is used in contradistinction to other qualifiers such  as &ldquo;multiple&rdquo; or &ldquo;partial.&rdquo; The word &ldquo;linear&rdquo; 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">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 &#x003c1; or its [[sample]] estimate ''r'' defined as follows, where the respective [[population]]  mean values of ''x'' and ''y'' are denoted by &#x003be; and &#x003b6;, the respective [[standard deviations]] by  &#x003c3;(''x'') and &#x003c3;('' 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'' - &#x003be;) (''y'' - &#x003b6;)] 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

  1. In general, a mutual relationship between variables or other entities.

    In statistical terminology, it is a form of statistical dependence.

  2. 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:
    ams2001glos-Ce41
    ams2001glos-Ce42

    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.


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