Difference between revisions of "Chi-squared distribution"

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* [[Normal]]
 
* [[Normal]]
 
* [[Rayleigh]]
 
* [[Rayleigh]]
 +
* [[F distribution]]
 
* [[Parametric continuous distributions]]
 
* [[Parametric continuous distributions]]
 
* [[Distribution Densities Library]]
 
* [[Distribution Densities Library]]

Revision as of 19:58, 4 August 2016


ChiSquared(d)

The ChiSquared distribution with «d» degrees of freedom describes the distribution of a Chi-Squared metric defined as

[math]\displaystyle{ \Chi^2 \sum_{i=1}^n {y_i}^2 }[/math]

where each yi is independently sampled from a standard normal distribution and d = n - 1 . The distribution is defined over nonnegative values.

The Chi-squared distribution is commonly used for analyses of second moments, such as analyses of variance and contingency table analyses. It can also be used to generate the F distribution.

Suppose

Variable V := ChiSquared(k)
Variable W := ChiSquared(m)
Variable S := (V/k)*(W/m)

S is distributed as an F distribution with k and m degrees of freedom.

The F distribution is useful for the analysis of ratios of variance, such as a one-factor between-subjects analysis of variance.

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