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forked from anonymous's block: nate central limit theorem demo
forked from anonymous's block: nate central limit theorem demo
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August 27, 2016 20:18
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nate central limit theorem demo
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| license: mit |
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| <!DOCTYPE html> | |
| <head> | |
| <!-- trying to demo what they did here with Java: http://onlinestatbook.com/2/sampling_distributions/clt_demo.html Except without Java --> | |
| <meta charset="utf-8"><!-- Load c3.css --> | |
| <link href="http://c3js.org/css/c3-b03125fa.css" rel="stylesheet" type="text/css"> | |
| <!-- Load d3.js and c3.js --> | |
| <script src="https://d3js.org/d3.v3.min.js"></script> | |
| <script src="http://c3js.org/js/c3.min-4c5bef8f.js"></script> | |
| <script src="https://d3js.org/d3-random.v1.min.js"></script> | |
| <script src="https://d3js.org/d3-array.v1.min.js"></script> | |
| </head> | |
| <body> | |
| <div id="chart"><div> | |
| <script> | |
| function getRandomSubarray(arr, size) { | |
| var shuffled = arr.slice(0), i = arr.length, min = i - size, temp, index; | |
| while (i-- > min) { | |
| index = Math.floor((i + 1) * Math.random()); | |
| temp = shuffled[index]; | |
| shuffled[index] = shuffled[i]; | |
| shuffled[i] = temp; | |
| } | |
| return shuffled.slice(min); | |
| } | |
| //histogram | |
| var t = 90; //number of thresholds | |
| //population | |
| var r = 100000; //population size; passed to range func | |
| var distribution = 'randomLogNormal'; | |
| var mu = 0; | |
| var sigma = 0.5; | |
| //sampling distribution | |
| var sample_size = 5; | |
| var num_samples = 1000; | |
| function getRandomSubarray(arr, size) { | |
| /* http://stackoverflow.com/a/11935263/1175496 */ | |
| var shuffled = arr.slice(0), i = arr.length, min = i - size, temp, index; | |
| while (i-- > min) { | |
| index = Math.floor((i + 1) * Math.random()); | |
| temp = shuffled[index]; | |
| shuffled[index] = shuffled[i]; | |
| shuffled[i] = temp; | |
| } | |
| return shuffled.slice(min); | |
| } | |
| function sample_dist(sample_size, num_samples, pop) { | |
| return d3 | |
| .range(num_samples) | |
| .map(function(){ | |
| return avg(getRandomSubarray(pop, sample_size)); | |
| }) | |
| } | |
| function avg(nums) { | |
| return nums | |
| .reduce(function(a,b) { | |
| return a+b })/nums.length | |
| } | |
| function sample_dist(s_size, num_samples, pop) { | |
| return d3 | |
| .range(num_samples) | |
| .map(function(){ | |
| //pointing at global variables; | |
| return avg(getRandomSubarray(pop, s_size)); }) | |
| } | |
| var pop=d3.range(r).map(d3[distribution](mu, sigma)); | |
| var pop_dist = d3.histogram().thresholds(40)(pop).map(function(d){return d.length}); | |
| var s_dist = d3.histogram().thresholds(40)(sample_dist(5,1000,pop)).map(function(d){return d.length}); | |
| var chart = c3.generate({ | |
| data: { | |
| columns: [ | |
| ['data1'].concat(pop_dist), | |
| //['data2', 130, 100, 140, 200, 150, 50] | |
| ], | |
| type: 'bar' | |
| }, | |
| bar: { | |
| width: { | |
| ratio: 0.90 // this makes bar width 50% of length between ticks | |
| } | |
| // or | |
| //width: 100 // this makes bar width 100px | |
| } | |
| }); | |
| </script> | |
| </body> |
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