Difference between revisions of "Expectation (math)"

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(New page: The '''expectation''' of random variable <math>X</math> with probability density function <math>f(x)</math> is :<math> \mbox{E}[X] =\int\limits_{-\infty}^\infty x f(x)dx. </math> This is a...)
 
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The '''expectation''' of random variable <math>X</math> with probability density function
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The mathematical '''expectation''' of a continuously distributed random variable <math>X</math> with [[probability density function]]
 
<math>f(x)</math> is
 
<math>f(x)</math> is
 
:<math>
 
:<math>
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f(x)dx.
 
f(x)dx.
 
</math>
 
</math>
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This is also the [[mean]] of random variable <math>X</math>.
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The expectation is also known as the [[mean]] of <math>X</math>.
  
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The expectation with respect to some function <math>g(X)</math> is
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The expectation with respect to some function <math>g(X)</math> where <math>X</math> is distributed according to <math>f(x)</math> is
 
:<math>
 
:<math>
 
\mbox{E}[g(X)]
 
\mbox{E}[g(X)]
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f(x)dx.
 
f(x)dx.
 
</math>
 
</math>
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For a discretely distributed random variable <math>X</math> with [[probability mass function]]
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<math>p_{k}</math> it is
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:<math>
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\mbox{E}[X]=\sum_{k} p_{k}x_{k}.
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</math>
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[[Category:Probability and Statistics]]

Latest revision as of 12:16, July 13, 2016

The mathematical expectation of a continuously distributed random variable <math>X</math> with probability density function <math>f(x)</math> is

<math>

\mbox{E}[X] =\int\limits_{-\infty}^\infty x f(x)dx. </math> The expectation is also known as the mean of <math>X</math>.

The expectation with respect to some function <math>g(X)</math> where <math>X</math> is distributed according to <math>f(x)</math> is

<math>

\mbox{E}[g(X)] =\int\limits_{-\infty}^\infty g(x) f(x)dx. </math>

For a discretely distributed random variable <math>X</math> with probability mass function <math>p_{k}</math> it is

<math>

\mbox{E}[X]=\sum_{k} p_{k}x_{k}. </math>