Design engineer, visualization researcher.
Published
Edited
Nov 6, 2020
Importers
expected = (kind, want) => ofKind.get(kind) * ofWant.get(want) / data.length
scaledError = (kind, want) => {
let expect = expected(kind, want)
return Math.pow(count.get(kind).get(want) - expect, 2) / expect
}
chiSq =
d3.sum(kinds.map(function(kind) {
return d3.sum(wants.map(function(want) {
return scaledError(kind, want)
}))
}))
chisqrprob(dof, chiSq)
d3 = require('d3@v6', 'd3-array@2')
// From statistics-distributions.js
// https://code.google.com/archive/p/statistics-distributions-js/
// via
// https://gist.github.com/yujiosaka/f94380bcb4b56780355c
chisqrprob = function chisqrprob ($n,$x) {
if (($n <= 0) || ((Math.abs($n) - (Math.abs(Math.floor($n)))) != 0)) {
throw("Invalid n: $n\n"); /* degree of freedom */
}
return _subchisqrprob($n-0, $x-0);
}
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
