(New page: ==Covariance, Correlation Coefficient== * <math>COV(X,Y)=E[(X-E[X])(Y-E[Y])]\!</math> * <math>COV(X,Y)=E[XY]-E[X]E[Y]\!</math>)
 
(Covariance, Correlation Coefficient)
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* <math>COV(X,Y)=E[(X-E[X])(Y-E[Y])]\!</math>
 
* <math>COV(X,Y)=E[(X-E[X])(Y-E[Y])]\!</math>
 
* <math>COV(X,Y)=E[XY]-E[X]E[Y]\!</math>
 
* <math>COV(X,Y)=E[XY]-E[X]E[Y]\!</math>
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==Markov Inequality==
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Loosely speaking: In a nonnegative RV has a small mean, then the probability that it takes a large value must also be small.
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* <math>P(X \leq a) \leq E[X]/a\!</math> 
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for all a > 0

Revision as of 06:13, 18 November 2008

Covariance, Correlation Coefficient

  • $ COV(X,Y)=E[(X-E[X])(Y-E[Y])]\! $
  • $ COV(X,Y)=E[XY]-E[X]E[Y]\! $

Markov Inequality

Loosely speaking: In a nonnegative RV has a small mean, then the probability that it takes a large value must also be small.

  • $ P(X \leq a) \leq E[X]/a\! $

for all a > 0

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Seraj Dosenbach