Beta Distribution


Statistics – Beta Distribution


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The beta distribution represents continuous probability distribution parametrized by two positive shape parameters, $ alpha $ and $ beta $, which appear as exponents of the random variable x and control the shape of the distribution.

Beta Distribution

Probability density function

Probability density function of Beta distribution is given as:

Formula

${ f(x) = frac{(x-a)^{alpha-1}(b-x)^{beta-1}}{B(alpha,beta) (b-a)^{alpha+beta-1}} hspace{.3in} a le x le b; alpha, beta > 0 \[7pt]
, where B(alpha,beta) = int_{0}^{1} {t^{alpha-1}(1-t)^{beta-1}dt} }$

Where −

  • ${ alpha, beta }$ = shape parameters.

  • ${a, b}$ = upper and lower bounds.

  • ${B(alpha,beta)}$ = Beta function.

Standard Beta Distribution

In case of having upper and lower bounds as 1 and 0, beta distribution is called the standard beta distribution. It is driven by following formula:

Formula

${ f(x) = frac{x^{alpha-1}(1-x)^{beta-1}}{B(alpha,beta)} hspace{.3in} le x le 1; alpha, beta > 0}$

Cumulative distribution function

Cumulative distribution function of Beta distribution is given as:

Formula

${ F(x) = I_{x}(alpha,beta) = frac{int_{0}^{x}{t^{alpha-1}(1-t)^{beta-1}dt}}{B(alpha,beta)}
hspace{.2in} 0 le x le 1; p, beta > 0 }$

Where −

  • ${ alpha, beta }$ = shape parameters.

  • ${a, b}$ = upper and lower bounds.

  • ${B(alpha,beta)}$ = Beta function.

It is also called incomplete beta function ratio.

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