Question

Ꮞ3
81a
2
10/12
$\sec(?) \cot( log_{ \beta \binom{ log_{ \beta \gamma e \gamma \gamma \gamma \gamma \gamma \beta \alpha \binom{ \binom{ \binom{ \binom{ \binom{ \binom{ \binom{ \binom{ \binom{ \binom{ \binom{ \binom{ \binom{ log_{ log_{ log_{\%e \infty \infty \%vhmcgtmv}(?) }(?) }(?) }{?} }{?} }{?} }{?} }{?} }{?} }{?} }{?} }{?} }{?} }{?} }{?} }{?} }(?) }{?} }(?) )$
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Answer 1

In probability theory and statistics, the beta-binomial distribution is a family of discrete probability distributions on a finite support of non-negative integers arising when the probability of success in each of a fixed or known number of Bernoulli trials is either unknown or random. The beta-binomial distribution is the binomial distribution in which the probability of success at each of n trials is not fixed but randomly drawn from a beta distribution. It is frequently used in Bayesian statistics, empirical Bayes methods and classical statistics to capture overdispersion in binomial type distributed data.