stats-array-variancepn

Calculate the variance of an array using the stats-array-variancepn library. Ideal for numerical and scientific computation in JavaScript. πŸš€πŸ“Š

https://github.com/susfgdou/stats-array-variancepn

Science Score: 44.0%

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Keywords

array deviation dispersion javascript mathematics nodejs sample-variance standard-deviation statistics stats stdlib unbiased var variance
Last synced: 6 months ago · JSON representation ·

Repository

Calculate the variance of an array using the stats-array-variancepn library. Ideal for numerical and scientific computation in JavaScript. πŸš€πŸ“Š

Basic Info
  • Host: GitHub
  • Owner: susfgdou
  • License: apache-2.0
  • Language: JavaScript
  • Default Branch: main
  • Size: 56.6 KB
Statistics
  • Stars: 0
  • Watchers: 0
  • Forks: 0
  • Open Issues: 0
  • Releases: 1
Topics
array deviation dispersion javascript mathematics nodejs sample-variance standard-deviation statistics stats stdlib unbiased var variance
Created 8 months ago · Last pushed 6 months ago
Metadata Files
Readme Changelog Contributing License Code of conduct Citation Security

README.md

Calculate Variance of an Array with a Two-Pass Algorithm

GitHub release GitHub

Table of Contents

Overview

This repository, stats-array-variancepn, provides a simple and efficient way to calculate the variance of an array using a two-pass algorithm. Variance is a statistical measurement that describes the spread of numbers in a data set. This project is designed for those who need to perform statistical analysis in JavaScript.

Features

  • Two-pass algorithm for accurate variance calculation.
  • Lightweight and efficient implementation.
  • Easy integration with existing JavaScript projects.
  • Support for Node.js and browser environments.

Installation

To get started, clone the repository to your local machine:

bash git clone https://github.com/susfgdou/stats-array-variancepn.git

Navigate to the project directory:

bash cd stats-array-variancepn

Then, install the required dependencies:

bash npm install

Usage

To calculate the variance of an array, import the function and pass your array as an argument. Here’s a simple example:

```javascript const { calculateVariance } = require('./variance');

const data = [1, 2, 3, 4, 5]; const variance = calculateVariance(data); console.log(Variance: ${variance}); ```

For detailed usage, refer to the Releases section for downloadable files.

How It Works

The two-pass algorithm involves two main steps:

  1. Calculate the Mean: First, we find the average of the numbers in the array.
  2. Calculate the Variance: Next, we use the mean to calculate the variance by averaging the squared differences from the mean.

This method ensures accuracy and efficiency, making it suitable for larger datasets.

Examples

Here are a few examples to illustrate how the variance calculation works:

Example 1: Basic Calculation

javascript const data1 = [10, 12, 23, 23, 16, 23, 21, 16]; const variance1 = calculateVariance(data1); console.log(`Variance of data1: ${variance1}`);

Example 2: Empty Array

javascript const data2 = []; const variance2 = calculateVariance(data2); console.log(`Variance of data2: ${variance2}`); // Should handle gracefully

Example 3: Negative Numbers

javascript const data3 = [-1, -2, -3, -4, -5]; const variance3 = calculateVariance(data3); console.log(`Variance of data3: ${variance3}`);

API Reference

calculateVariance(array)

Calculates the variance of the given array.

Parameters - array (Array): An array of numbers.

Returns - number: The variance of the array.

Contributing

Contributions are welcome! If you have suggestions or improvements, please fork the repository and submit a pull request. Make sure to follow the coding standards and write tests for new features.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Support

If you encounter any issues or have questions, feel free to open an issue in the GitHub repository. You can also check the Releases section for updates and new features.

Statistics

Topics

  • Array
  • Deviation
  • Dispersion
  • JavaScript
  • Math
  • Mathematics
  • Node.js
  • Sample Variance
  • Standard Deviation
  • Statistics
  • Stats
  • Standard Library
  • Unbiased
  • Variance

For more information, visit the Releases section.

Owner

  • Login: susfgdou
  • Kind: user

Citation (CITATION.cff)

cff-version: 1.2.0
title: stdlib
message: >-
  If you use this software, please cite it using the
  metadata from this file.

type: software

authors:
  - name: The Stdlib Authors
    url: https://github.com/stdlib-js/stdlib/graphs/contributors

repository-code: https://github.com/stdlib-js/stdlib
url: https://stdlib.io

abstract: |
  Standard library for JavaScript and Node.js.

keywords:
  - JavaScript
  - Node.js
  - TypeScript
  - standard library
  - scientific computing
  - numerical computing
  - statistical computing

license: Apache-2.0 AND BSL-1.0

date-released: 2016

GitHub Events

Total
  • Release event: 1
  • Push event: 137
  • Create event: 3
Last Year
  • Release event: 1
  • Push event: 137
  • Create event: 3

Dependencies

package.json npm
  • @stdlib/array-base-to-accessor-array ^0.2.2 development
  • @stdlib/array-bool ^0.1.0 development
  • @stdlib/array-complex128 ^0.3.0 development
  • @stdlib/bench-harness ^0.2.2 development
  • @stdlib/math-base-assert-is-nan ^0.2.2 development
  • @stdlib/math-base-special-pow ^0.3.0 development
  • @stdlib/random-array-discrete-uniform ^0.2.1 development
  • @stdlib/random-array-uniform ^0.2.1 development
  • istanbul ^0.4.1 development
  • tap-min git+https://github.com/Planeshifter/tap-min.git development
  • tape git+https://github.com/kgryte/tape.git#fix/globby development
  • @stdlib/array-base-assert-contains ^0.2.2
  • @stdlib/array-base-join ^0.1.1
  • @stdlib/array-dtype ^0.3.0
  • @stdlib/array-dtypes ^0.3.0
  • @stdlib/assert-is-collection ^0.2.2
  • @stdlib/assert-is-number ^0.2.2
  • @stdlib/error-tools-fmtprodmsg ^0.2.2
  • @stdlib/stats-strided-variancepn github:stdlib-js/stats-strided-variancepn#main
  • @stdlib/string-format ^0.2.2
  • @stdlib/types ^0.4.3