Error function: Difference between revisions

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In [[mathematics]], the '''error function''' is a [[function (mathematics)|function]] associated with the [[cumulative distribution function]] of the [[normal distribution]].
In [[mathematics]], the '''error function''' is a [[function (mathematics)|function]] associated with the [[cumulative distribution function]] of the [[normal distribution]].


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:<math>\operatorname{erf}(x) = \frac{2}{\sqrt\pi} \int_{0}^{x} \exp(-t^2) dt .\,</math>
:<math>\operatorname{erf}(x) = \frac{2}{\sqrt\pi} \int_{0}^{x} \exp(-t^2) dt .\,</math>
The '''complementary error function''' is defined as
:<math>\operatorname{erfc}(x) = 1 - \operatorname{erf}(x) .\,</math>


The probability that a normally distributed random variable ''X'' with mean μ and variance σ<sup>2</sup> exceeds ''x'' is
The probability that a normally distributed random variable ''X'' with mean μ and variance σ<sup>2</sup> exceeds ''x'' is


:<math>F(x;\mu,\sigma)=\frac{1}{2} \left[ 1 + \operatorname{erf} \left( \frac{x-\mu}{\sigma\sqrt{2}} \right) \right].
:<math>F(x;\mu,\sigma)=\frac{1}{2} \left[ 1 + \operatorname{erf} \left( \frac{x-\mu}{\sigma\sqrt{2}} \right) \right].
</math>
</math>[[Category:Suggestion Bot Tag]]

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In mathematics, the error function is a function associated with the cumulative distribution function of the normal distribution.

The definition is

The complementary error function is defined as

The probability that a normally distributed random variable X with mean μ and variance σ2 exceeds x is