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https://github.com/vweevers/student-histogram
Record a sample and compute its statistical significance.
https://github.com/vweevers/student-histogram
histogram nodejs npm-package statistics student-t
Last synced: 19 days ago
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Record a sample and compute its statistical significance.
- Host: GitHub
- URL: https://github.com/vweevers/student-histogram
- Owner: vweevers
- License: other
- Created: 2017-10-24T10:10:35.000Z (about 7 years ago)
- Default Branch: main
- Last Pushed: 2023-11-01T02:34:55.000Z (about 1 year ago)
- Last Synced: 2024-12-15T10:50:41.332Z (24 days ago)
- Topics: histogram, nodejs, npm-package, statistics, student-t
- Language: JavaScript
- Homepage:
- Size: 19.5 KB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 5
-
Metadata Files:
- Readme: readme.md
- License: LICENSE
Awesome Lists containing this project
README
# student-histogram
**Record a sample and compute its statistical significance.** Uses [`native-hdr-histogram`][native-hdr-histogram] and a two-tailed t-distribution table under the hood. Good for sample sizes below 200. HDR histogram is designed for "value measurements in latency and performance sensitive applications", quantizes values with a configurable precision and has a constant memory footprint.
[](https://www.npmjs.com/package/student-histogram)
[](https://www.npmjs.com/package/student-histogram)
[](https://github.com/vweevers/student-histogram/actions/workflows/test.yml)
[](https://standardjs.com)
## Example
```js
const StudentHistogram = require('student-histogram')
const h = new StudentHistogram(1, 200, 3)
// Record some example values.
const sample = [100, 120, 101, 103, 99]
sample.forEach(v => h.record(v))
const log = console.log
const percent = require('fixed-number')(1, 2, 'percent')
log('arithmetic mean : %d ±%s', h.mean(), percent(h.rme()))
log('standard deviation :', h.stddev())
log('minimum and maximum : %d and %d', h.min(), h.max())
log('75% of values fall below :', h.percentile(75))
log()
log('standard error of the mean :', h.sem())
log('margin of error :', h.moe())
log('relative margin of error :', h.rme())
log('with higher confidence :', h.rme(0.998))
log()
// Estimate the size (number of sampling points aka recorded values)
// that is required to achieve a relative margin of error of 0.05.
log('recommended sample size :', h.minimumSize(0.05))
log('for 99.5% confidence :', h.minimumSize(0.05, 0.995))
log('with 10% error tolerance :', h.minimumSize(0.10))
if (h.size < h.minimumSize(0.05)) {
// Maybe record some more!
}
```
Output:
```
arithmetic mean : 104.6 ±9.27%
standard deviation : 7.812809993849844
minimum and maximum : 99 and 120
75% of values fall below : 103
standard error of the mean : 3.493994848307593
margin of error : 9.700727296841201
relative margin of error : 0.09274117874609179
with higher confidence : 0.23960921458776316
recommended sample size : 18
for 99.5% confidence : 70
with 10% error tolerance : 5
```
## API
### `StudentHistogram(min, max, figures, opts)`
Documentation to follow.
## Install
With [npm](https://npmjs.org) do:
```
npm install student-histogram
```
## See also
- [`hdr-histogram-percentiles-obj`][hdr-histogram-percentiles-obj] (`student-histogram` is compatible)
## License
[MIT](LICENSE) © 2017-present Vincent Weevers. Based in part on [`benchmark.js`][benchmark-js] and [`sample-sizer`][sample-sizer]. See included [`LICENSE`](LICENSE) file for all copyright owners.
[benchmark-js]: https://github.com/bestiejs/benchmark.js
[sample-sizer]: https://github.com/mapbox/sample-sizer
[native-hdr-histogram]: https://github.com/mcollina/native-hdr-histogram
[hdr-histogram-percentiles-obj]: https://github.com/thekemkid/hdr-histogram-percentiles-obj