Difference between revisions of "Beta distribution"
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* [[BetaI]] -- the incomplete beta function, gives the cumulative density analytically. | * [[BetaI]] -- the incomplete beta function, gives the cumulative density analytically. | ||
* [[BetaIInv]] -- the inverse of [[BetaI]]. | * [[BetaIInv]] -- the inverse of [[BetaI]]. | ||
+ | * [[Dens_Beta]] -- the probability density of Beta(a,b) at x | ||
* [[Pert]] - A parametric variation on the beta distribution | * [[Pert]] - A parametric variation on the beta distribution |
Revision as of 20:04, 3 October 2007
Beta(X,Y,lower,upper)
The Beta distribution.
Creates a continuous distribution of numbers between 0 and 1 with X / (X+Y) representing the mean, if the optional parameters lower and upper are omitted. For bounds other than 0 and 1, specify the optional lower and upper bounds to offset and expand the distribution.
X and Y must be positive.
When to use
Use a beta distribution if the uncertain quantity is bounded by 0 and 1 (or 100%), is continuous, and has a single mode. This distribution is particularly useful for modeling an opinion about the fraction of a population that has some characteristic. For example, if you have observed n members of the population, of which r display the characteristic c, you can represent the uncertainty about the true fraction with c using a beta distribution with parameters X = r and Y = n - r.
If the uncertain quantity has lower and upper bounds other than 0 and 1, include the lower and upper bounds parameters to obtain a transformed beta distribution. The transformed beta is a very flexible distribution for representing a wide variety of bounded quantities.
Library
Distributions
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