Binomial Distribution Probability Calculator API

By for April 22, 2015

Report Abuse
Calculate the probability given a quantile and a binomial distribution.
> **Note:** This is depreciated. The Binomial Distribution Probability Calculator API is an example built with Microsoft Azure Machine Learning that helps generate and handle binomial distributions. This service is a part of the Binomial distribution suite of services that allows the user to generate a binomial distribution sequence of any length, calculate quantiles out of given probability and calculate probability from a given quantile (this specific service). Each of the services emit different outputs based on the selected service (see description below). The Binomial Distribution Suite is based on R functions qbinom, rbinom and pbinom that are included in R stats package. ##Consumption of Web Service## This service accepts 4 arguments of a binomial distribution and calculates the associated probability. The following arguments should be provided within the request: - q - a single quantile of an event with binomial distribution, - size - the number of trials, - prob - the probability of success in a trial, - side - L for the lower side of the distribution, U for the upper side of the distribution or E that is equal to a single number of successes. The output of the service is the calculated probability that is associated with the given quantile. ##Example Application There are multiple ways of consuming the service in an automated fashion. One example apps is here: [Probability Calculator](http://microsoftazuremachinelearning.azurewebsites.net/BinomialDistributionProbabilityCalculator.aspx). *While these web services could be consumed by users - potentially directly on the marketplace, through a mobile app, website, or even on a local computer for example, the purpose of the web service is also to serve as an example of how Azure ML can be used to create web services on top of R code. With just a few lines of R code and clicks of a button within the Azure ML Studio, an experiment can be created with R code and published as a web service. The web service can then be published to the Azure Marketplace and consumed by users and devices across the world with no infrastructure set-up by the author of the web service.*