1Blurb::
2Aleatory uncertain discrete variable - binomial
3Description::
4The binomial distribution describes probabilities associated with a series
5of independent Bernoulli trials.
6A Bernoulli trial is an event with two mutually exclusive outcomes,
7such as 0 or 1, yes or no, success or fail.
8The probability of success remains the same (the trials are independent).
9
10The density function for the binomial distribution is given by:
11\f[f(x) = \left(\begin{array}{c}n\\x\end{array}\right){p^x}{(1-p)^{(n-x)}}\f]
12where \c p is the
13probability of failure per trial,  \c n is the number of trials and
14\c x is the number of successes.
15
16Topics::	discrete_variables, aleatory_uncertain_variables
17Examples::
18Theory::
19The binomial distribution is typically used to predict the number of failures
20or defective items in a total of \c n independent tests or trials,
21where each trial has the probability \c p of failing or being defective.
22
23Faq::
24See_Also::
25