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[](https://travis-ci.org/erictheise/mctad.js) [](https://gemnasium.com/erictheise/mctad.js) mctad.js ======== Measures of Central Tendency And Dispersion: A JavaScript library for probability & statistics ### About __mctad.js__ is a JavaScript library for probability and statistics. A goal is to provide functionality missing from other such libraries, including the ability to generate random variables from many common discrete and continuous probability distributions, and having a basic implementation of directional statistics. ### Use You'll want either the file `mctad.min.js` or the file `mctad.js` in the root of this repository. ### Documentation See the [GitHub pages](http://erictheise.github.io/mctad.js/) for examples of using _mctad.js_. In addition, _mctad.js_ runs [groc](http://nevir.github.io/groc/) as a [grunt](http://gruntjs.com/) task to automatically generate html documentation from comments in the source code. Access that documentation by opening a browser on your local copy of `/doc/index.html` after you `git clone` this repository or look at the [`/doc/` directory](http://erictheise.github.io/mctad.js/doc/) of the GitHub pages. #### Continuous and Discrete Probability Distributions Distributions can be called by their common names and required parameters, e.g., `mctad.poisson(7)`. This returns an object containing: * statistics on the distribution, including * _mean_ * _median_ * _mode_ * _variance_ * _skewness_ * _entropy_ * _pdf_, the _probability density function_ (continuous distributions), or _pmf_, the _probability mass function_ (discrete distributions) * _cdf_, the _cumulative_distribution_function_ * convenience methods to access _pmf_ as _P(X)_ and _cdf_ as _F(X)_ * _generate(n)_, a method for generating _n_ random variables from the distribution making it possible to say things such as * `mctad.poisson(7).mean` * `mctad.poisson(7).P(5)` * `mctad.poisson(7).F(2)` * `mctad.triangular(3, 9, 4).generate(36)` * `mctad.normal(60.2, 4.5).generate(100)` Statistics on the distributions will return `undefined` if not implemented (this _is_ version 0.0.X after all ) or if actually not defined for the distribution. Since there need not be a single mode, `mode` always returns an Array. ### Tests _mctad.js_ uses [mocha]() with [chai assertions]() as a [grunt](http://gruntjs.com/) task to run the test suite. The general format of the tests is to test exceptions before testing functionality. When possible, test data is taken from a wikipedia article or other hopefully long-lived reference. If these are not available, hand-worked examples are used for testing. ### Conventions The ability to use Greek letters directly in code appeals to me, and they are used internally. I am still considering the extent to which they should be exposed externally. In an ideal world, it would be reliable to use constructions such as p-hat (p) and x-bar (x) as variable names. You will come across examples of _type hinting_, e.g., in the form of 1 versus 1.0, to help clarify whether quantities are expected to take integer or real values. ### To Do * "self-estimating" distributions * chi square goodness of fit * analysis of variance

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