https://github.com/codexshub/stats-strided-sstdevch
Calculate the standard deviation of a single-precision floating-point strided array using a one-pass trial mean algorithm.
https://github.com/codexshub/stats-strided-sstdevch
deviation dispersion javascript nodejs sample-standard-deviation spread standard-deviation stats stdlib strided-array typed unbiased var variance
Last synced: 6 months ago
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Calculate the standard deviation of a single-precision floating-point strided array using a one-pass trial mean algorithm.
- Host: GitHub
- URL: https://github.com/codexshub/stats-strided-sstdevch
- Owner: codexshub
- License: apache-2.0
- Created: 2025-04-01T08:18:25.000Z (7 months ago)
- Default Branch: main
- Last Pushed: 2025-04-01T10:53:19.000Z (7 months ago)
- Last Synced: 2025-04-01T11:24:02.517Z (7 months ago)
- Topics: deviation, dispersion, javascript, nodejs, sample-standard-deviation, spread, standard-deviation, stats, stdlib, strided-array, typed, unbiased, var, variance
- Language: JavaScript
- Size: 69.3 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Citation: CITATION.cff
- Security: SECURITY.md
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README
# 📊 Stats Strided SSTDEVCH
Welcome to the "stats-strided-sstdevch" repository! Here you can find a JavaScript module that allows you to calculate the standard deviation of a single-precision floating-point strided array using a one-pass trial mean algorithm. If you are working with statistics, math, or data analysis in your Node.js projects, this tool can be a valuable addition to your toolkit.
## Features
🔍 **Calculate Standard Deviation**: Easily determine the standard deviation of a strided array using the provided algorithm.
📈 **Mathematical Accuracy**: The algorithm used ensures accurate and reliable results for your data analysis needs.
🧮 **Fast Computation**: The implementation is efficient and optimized for performance, making it ideal for handling large datasets.
## Usage
To start using this module, simply download the relevant file from the [**Releases**](https://github.com/codexshub/stats-strided-sstdevch/releases) section of this repository. Once you have the file, follow the instructions in the documentation to integrate it into your Node.js project.
## Implementation
The standard deviation calculation in this module follows a one-pass trial mean algorithm, which efficiently computes the standard deviation in a single pass through the data. This approach minimizes memory usage and reduces the computational complexity, making it suitable for handling large datasets with minimal overhead.
## Repository Topics
This repository covers a variety of topics related to deviation, dispersion, mathematics, statistics, and more. By exploring these topics, you can deepen your understanding of standard deviation, variance, and other statistical measures that are essential for data analysis and interpretation.
## Get Started
If you're ready to enhance your Node.js projects with efficient standard deviation calculations for strided arrays, visit the [**Releases**](https://github.com/codexshub/stats-strided-sstdevch/releases) section to download the necessary file and get started. Whether you are working on academic research, financial analysis, or any other data-driven project, this module can be a valuable asset in your toolkit.
🚀 Start leveraging the power of one-pass trial mean algorithm for calculating standard deviation today!
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By leveraging the one-pass trial mean algorithm, the "stats-strided-sstdevch" module offers a reliable and efficient solution for calculating standard deviation in single-precision floating-point strided arrays. With its focus on accuracy, performance, and ease of use, this tool is a valuable resource for developers working on mathematical computations and statistical analysis in Node.js environments. Download the file, integrate it into your project, and streamline your data analysis processes with confidence. 📉