Difference between revisions of "Binomial distribution"

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= See Also =
 
= See Also =
  
 +
* [[CumBinomial]] -- the analytica cumulative probability function for Binomial
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* [[Prob_Binomial]] -- the analytic probability function for Binomial
 
* [[Multinomial]] -- A generalization of Binomial in which more than two outcomes are possible.
 
* [[Multinomial]] -- A generalization of Binomial in which more than two outcomes are possible.

Revision as of 19:58, 23 January 2012


Binomial( n,p )

Consider an event—such as a coin coming down heads—that can be true or false in each trial—or each toss—with probability p -- it has a Bernoulli distribution. A binomial distribution describes the number of times an event is true -- e.g., the coin is heads -- in n independent trials—or tosses—where the event occurs with probability p on each trial.

Library

Distributions

See Also

  • CumBinomial -- the analytica cumulative probability function for Binomial
  • Prob_Binomial -- the analytic probability function for Binomial
  • Multinomial -- A generalization of Binomial in which more than two outcomes are possible.
Comments


Marksmith

97 months ago
Score 0
It would still be useful to have a built-in function, say Binomial(n,p,k1,k2) that samples from the conditional Binomial distribution X|k1<=X<=k2. UDFs for the conditional Poisson are easier to write and operate quicker than for the conditional Binomial.

Lchrisman

74 months ago
Score 0
Mark -- Try: Truncate( Binomial(n, p), k1, k2 )

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