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simple-statistics

Advanced tools

The simple-statistics npm package provides a comprehensive set of statistical tools and functions for performing various statistical analyses. It is designed to be easy to use and covers a wide range of statistical operations, from basic descriptive statistics to more complex regression analysis.

Descriptive Statistics

This feature allows you to calculate basic descriptive statistics such as mean, median, and variance. The code sample demonstrates how to compute these statistics for a given dataset.

```
const ss = require('simple-statistics');
const data = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10];
const mean = ss.mean(data);
const median = ss.median(data);
const variance = ss.variance(data);
console.log(`Mean: ${mean}, Median: ${median}, Variance: ${variance}`);
```

Probability Distributions

This feature provides functions to work with various probability distributions, including normal and binomial distributions. The code sample shows how to generate a random normal value and a binomial distribution.

```
const ss = require('simple-statistics');
const normal = ss.randomNormal(0, 1);
const binomial = ss.binomialDistribution(10, 0.5);
console.log(`Random Normal Value: ${normal}, Binomial Distribution: ${binomial}`);
```

Regression Analysis

This feature allows you to perform regression analysis, including linear regression. The code sample demonstrates how to compute a linear regression line for a given dataset.

```
const ss = require('simple-statistics');
const data = [[0, 1], [1, 2], [2, 3], [3, 4], [4, 5]];
const regression = ss.linearRegression(data);
const regressionLine = ss.linearRegressionLine(regression);
console.log(`Regression Line: y = ${regression.m}x + ${regression.b}`);
```

Hypothesis Testing

This feature provides functions for performing hypothesis testing, such as t-tests. The code sample shows how to perform a two-sample t-test on two datasets.

```
const ss = require('simple-statistics');
const tTest = ss.tTestTwoSample([1, 2, 3, 4, 5], [6, 7, 8, 9, 10]);
console.log(`T-Test Result: ${tTest}`);
```

jstat is a JavaScript library for statistical operations. It offers a wide range of statistical functions similar to simple-statistics, including descriptive statistics, probability distributions, and hypothesis testing. However, jstat has a more extensive API and supports matrix operations, making it suitable for more complex statistical analyses.

mathjs is a comprehensive mathematics library for JavaScript and Node.js. It includes a variety of mathematical functions, including statistical operations. While it is not solely focused on statistics like simple-statistics, it provides a broader range of mathematical tools, making it a versatile choice for projects that require both statistical and general mathematical computations.

ssjs (Statistical Software in JavaScript) is another library that provides statistical functions for JavaScript. It offers similar functionalities to simple-statistics, such as descriptive statistics and probability distributions. However, ssjs is less popular and has a smaller community compared to simple-statistics, which may affect the availability of support and updates.

A JavaScript implementation of descriptive, regression, and inference statistics.

Implemented in literate JavaScript with no dependencies, designed to work in all modern browsers (including IE) as well as in node.js.

- :green_book: API Documentation
- :chart_with_upwards_trend: Benchmarks
- :kissing: A list of other statistics libraries

**I'm using Node.js, Webpack, Browserify, Rollup, or another module bundler, and install packages from npm.**- First, install the
`simple-statistics`

module, using`npm install simple-statistics`

, then include the code with require or import: **I use the**`require`

function to use modules in my project. (most likely)- When you use
`require`

, you have the freedom to assign the module to any variable name you want, but you need to specify the module's name exactly: in this case, 'simple-statistics'. The`require`

method returns an object with all of the module's methods attached to it.

var ss = require('simple-statistics')

- When you use
**I use**`import`

to use modules in my project. I'm probably using Babel,`@std/esm`

, Webpack, or Rollup.- Import all functions under the ss object:
import * as ss from 'simple-statistics'

Include a specific named export:import {min} from 'simple-statistics'

Simple statistics has*only*named exports for ES6.

- Import all functions under the ss object:

- First, install the
**I'm using Deno.**- Simple Statistics is published for Deno: https://deno.land/x/simplestatistics

**I'm not using a module bundler. I'm writing a web page, and want to include simple-statistics using a script tag.****I want to support all browsers**- When you use simple-statistics from a script tag, you don't get to choose
the variable name it is assigned to: simple-statistics will always become
available globally as the variable
`ss`

. You can reassign this variable to another name if you want to, but doing so is optional.`<script src='https://unpkg.com/simple-statistics@7.8.3/dist/simple-statistics.min.js'> </script>`

- When you use simple-statistics from a script tag, you don't get to choose
the variable name it is assigned to: simple-statistics will always become
available globally as the variable
**I want to use ES6 modules in a browser and I'm willing to only support new browsers to do it**- This module works great with the
`?module`

query parameter of unpkg. If you specify`type='module'`

in your script tag, you'll be able to import simple-statistics directly - through`index.js`

and with true ES6 import syntax and behavior.

This feature is still experimental in unpkg and very bleeding-edge.`<script type='module'> import {min} from "https://unpkg.com/simple-statistics@7.8.3/index.js?module" console.log(min([1, 2, 3])) </script>`

- This module works great with the

FAQs

Simple Statistics

The npm package simple-statistics receives a total of **173,841** weekly downloads. As such, simple-statistics popularity was classified as **popular**.

We found that simple-statistics demonstrated a **healthy** version release cadence and project activity because the last version was released less than a year ago. It has **1 open source maintainer** collaborating on the project.

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