Skip to content

Normalize a sample drawn from different populations and convert into a Z-score

Notifications You must be signed in to change notification settings

snlamm/normalize-samples

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

4 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

normalize-samples

Build Status Coverage Status NPM Version License

A light tool to normalize a sample drawn from multiple populations. Outputs include a normalized Z-score and confidence intervals for the sample.

Example

const normalize = require('normalize-samples')

// For each population, provide the population mean and standard deviation.
// Use whichever population names you want.
// There's no limit on the number of populations or sample sizes.
const samples = {
	popuplationNameA: {
		mean: 43.93,
		sd: 30.746,
		sample: [ 20,  42,  30, ..., 21,  89, 29 ]
	},
	popuplationNameB: {
		mean: 490.14,
		sd: 290.043,
		sample: [ 632,  606,  836,, ..., 306,  191,  773 ]
	}
}

const sampleResults = normalize(samples)
return sampleResults
// All results are normalized
/*
{
	samples: [ -0.7783126260326547, -0.0627723931568334, ..., 1.4691109994977396],
	n: 50,
	mean: 0.060919568506139964,
	standardError: 0.14142135623,
	zScore: 0.182759,
	proportion: 0.5714,
	confidenceInterval95: {
		low: -0.2162662897,
		high: 0.33810542671,
		marginOfError: 0.27718585821
	},
	confidenceInterval98: {
		low: -0.2685921915,
		high: 0.39043132851,
		marginOfError: 0.32951176001
	}
}
*/

Installation

This plugin is compatible with Node versions >= 4.8.6.

Add the normalize-samples package via your preferred package manager:

npm install --save normalize-samples

Contributing

Contributions are always welcome. You are encouraged to open issues and merge requests.

To run the tests, use npm run test.

About

Normalize a sample drawn from different populations and convert into a Z-score

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published