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Works with numeric arrays, and will automatically filter out non-numeric values and attempt to convert string numeric values.\n\n## Install\n\n```\n npm install stats-lite --save\n```\n\nExample\n---\n\n[Live Demo using Browserify!](http://requirebin.com/embed?gist=brycebaril/9591291)\n\n```javascript\nvar stats = require(\"stats-lite\")\n\nvar dice = require(\"dice\")\n\nvar rolls = []\nfor (var i = 0; i < 3000; i++) {\n  rolls.push(dice.sum(dice.roll(\"2d6\")))\n}\n\nconsole.log(\"sum: %s\", stats.sum(rolls))\nconsole.log(\"mean: %s\", stats.mean(rolls))\nconsole.log(\"median: %s\", stats.median(rolls))\nconsole.log(\"mode: %s\", stats.mode(rolls))\nconsole.log(\"variance: %s\", stats.variance(rolls))\nconsole.log(\"standard deviation: %s\", stats.stdev(rolls))\nconsole.log(\"sample standard deviation: %s\", stats.sampleStdev(rolls))\nconsole.log(\"85th percentile: %s\", stats.percentile(rolls, 0.85))\nconsole.log(\"histogram:\", stats.histogram(rolls, 10))\n\n/* Your exact numbers may vary, but they should be pretty similar:\nsum: 21041\nmean: 7.0136666666666665\nmedian: 7\nmode: 7\nvariance: 5.8568132222220415\nstandard deviation: 2.4200853749861886\nsample standard deviation: 2.4204888234135953\n85th percentile: 10\nhistogram { values: [ 94, 163, 212, 357, 925, 406, 330, 264, 164, 85 ],\n  bins: 10,\n  binWidth: 1.05,\n  binLimits: [ 1.75, 12.25 ] }\n*/\n\n```\n\n**Compatibility Notice**: Version 2.0.0+ of this library use features that require Node.js v4.0.0 and above\n\nAPI\n===\n\nAll of the exported functions take `vals` which is an array of numeric values. Non-numeric values will be removed, and string numbers will be converted to Numbers.\n\n**NOTE**: This will impact some operations, e.g. `mean([null, 1, 2, 3])` will be calculated as `mean([1, 2, 3])`, (e.g. `6 / 3 = 2`, NOT `6 / 4 = 1.5`)\n\n`numbers(vals)`\n---\n\nAccepts an array of values and returns an array consisting of only numeric values from the source array. Converts what it can and filters out anything else. e.g.\n\n```js\nnumbers([\"cat\", 1, \"22.9\", 9])\n// [1, 22.9, 9]\n```\n\n`sum(vals)`\n---\n\n[Sum](http://en.wikipedia.org/wiki/Summation) the values in the array.\n\n`mean(vals)`\n---\n\nCalculate the [mean](http://en.wikipedia.org/wiki/Mean) average value of `vals`.\n\n`median(vals)`\n---\n\nCalculate the [median](http://en.wikipedia.org/wiki/Median) average value of `vals`.\n\n`mode(vals)`\n---\n\nCalculate the [mode](http://en.wikipedia.org/wiki/Mode_statistics) average value of `vals`.\n\nIf `vals` is multi-modal (contains multiple modes), `mode(vals)` will return a ES6 Set of the modes.\n\n`variance(vals)`\n---\n\nCalculate the [variance](http://en.wikipedia.org/wiki/Variance) from the mean for a population.\n\n`stdev(vals)`\n---\n\nCalculate the [standard deviation](http://en.wikipedia.org/wiki/Standard_deviation) of the values from the mean for a population.\n\n`sampleVariance(vals)`\n---\n\nCalculate the [variance](http://en.wikipedia.org/wiki/Variance) from the mean for a sample.\n\n`sampleStdev(vals)`\n---\n\nCalculate the [standard deviation](http://en.wikipedia.org/wiki/Standard_deviation) of the values from the mean for a sample.\n\n\n`percentile(vals, ptile)`\n---\n\nCalculate the value representing the desired [percentile](http://en.wikipedia.org/wiki/Percentile) `(0 < ptile <= 1)`. Uses the Estimation method to interpolate non-member percentiles.\n\n`histogram(vals[, bins])`\n---\n\nBuild a histogram representing the distribution of the data in the provided number of `bins`. If `bins` is not set, it will choose one based on `Math.sqrt(vals.length)`. Data will look like:\n```\nhistogram {\n  values: [ 86, 159, 253, 335, 907, 405, 339, 270, 146, 100 ],\n  bins: 10,\n  binWidth: 1.05,\n  binLimits: [ 1.75, 12.25 ]\n}\n```\nWhere `values` are the bins and the counts of the original values falling in that range. The ranges can be calculated from the `binWidth` and `binLimits`. For example, the first bin `values[0]` in this example is from `1.75 < value <= 2.8`. The third bin `values[2]` would be `1.75 + (1.05 * 2) < value <= 1.75 + (1.05 * 3)` or `3.85 < value <= 4.9`.\n\nLICENSE\n=======\n\nMIT\n","maintainers":[{"name":"bryce","email":"bryce@ravenwall.com"}],"time":{"modified":"2022-06-27T00:07:19.619Z","created":"2013-08-21T06:33:39.930Z","1.0.0":"2013-08-21T06:33:41.959Z","1.0.1":"2014-01-30T18:32:31.934Z","1.0.2":"2014-03-17T00:19:37.301Z","1.0.3":"2014-03-17T00:25:15.962Z","2.0.0":"2015-09-09T23:55:15.281Z","2.0.1":"2016-03-18T21:02:18.318Z","2.0.2":"2016-07-20T20:55:36.059Z","2.0.3":"2016-07-21T06:22:25.052Z","2.0.4":"2017-03-05T05:02:36.631Z","2.1.0":"2017-07-11T19:34:12.601Z","2.1.1":"2018-05-01T18:52:35.967Z","2.2.0":"2018-09-11T16:03:18.123Z"},"author":{"name":"Bryce B. 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