.. _variables-binomial_uncertain: """""""""""""""""" binomial_uncertain """""""""""""""""" Aleatory uncertain discrete variable - binomial **Topics** discrete_variables, aleatory_uncertain_variables .. toctree:: :hidden: :maxdepth: 1 variables-binomial_uncertain-probability_per_trial variables-binomial_uncertain-num_trials variables-binomial_uncertain-initial_point variables-binomial_uncertain-descriptors **Specification** - *Alias:* None - *Arguments:* INTEGER - *Default:* no binomial uncertain variables **Child Keywords:** +-------------------------+--------------------+---------------------------+---------------------------------------------+ | Required/Optional | Description of | Dakota Keyword | Dakota Keyword Description | | | Group | | | +=========================+====================+===========================+=============================================+ | Required | `probability_per_trial`__ | A distribution parameter for the binomial | | | | distribution | +----------------------------------------------+---------------------------+---------------------------------------------+ | Required | `num_trials`__ | A distribution parameter | +----------------------------------------------+---------------------------+---------------------------------------------+ | Optional | `initial_point`__ | Initial values for variables | +----------------------------------------------+---------------------------+---------------------------------------------+ | Optional | `descriptors`__ | Labels for the variables | +----------------------------------------------+---------------------------+---------------------------------------------+ .. __: variables-binomial_uncertain-probability_per_trial.html __ variables-binomial_uncertain-num_trials.html __ variables-binomial_uncertain-initial_point.html __ variables-binomial_uncertain-descriptors.html **Description** The binomial distribution describes probabilities associated with a series of independent Bernoulli trials. A Bernoulli trial is an event with two mutually exclusive outcomes, such as 0 or 1, yes or no, success or fail. The probability of success remains the same (the trials are independent). The density function for the binomial distribution is given by: .. math:: f(x) = \left(\begin{array}{c}n\\x\end{array}\right){p^x}{(1-p)^{(n-x)}}, where :math:`p` is the probability of failure per trial, :math:`n` is the number of trials and :math:`x` is the number of successes. **Theory** The binomial distribution is typically used to predict the number of failures or defective items in a total of :math:`n` independent tests or trials, where each trial has the probability :math:`p` of failing or being defective.