2b:null 2c:["$","title",null,{"children":"Quartet d'Anscombe | Anders | Observable"}] 31:T5ed,html` ${['A', 'B', 'C', 'D'].map(d => html``)} ${ data .map(set => math.mean(set.map(d => d[0]))) .map(d => html``) } ${ data .map(set => math.var(set.map(d => d[0]))) .map(d => html``) } ${ data .map(set => math.mean(set.map(d => d[1]))) .map(d => Math.round(d * 100) / 100) .map(d => html``) } ${ data .map(set => math.var(set.map(d => d[1]))) .map(d => Math.round(d * 100) / 100) .map(d => html``) } ${ data .map(set => set.reduce(({ x, y }, d) => ({ x: [...x, d[0]], y: [...y, d[1]] }), {x: [], y: []})) .map(({ x, y }) => getCorrelation(x, y)) .map(d => Math.round(d * 100) / 100) .map(d => html``) } ${ data .map(set => regression.linear(set).string) .map(d => html``) } ${ data .map(set => regression.linear(set).r2) .map(d => html``) }

	${d}
Moyenne des X	${d}
Variance des X	${d}
Moyenne des Y	${d}
Variance des Y	${d}
Coefficient de corrélation	${d}
Régression linéaire	${d}
Coefficient de détermination	${d}

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${d}
x	y	x	y	x	y	x	y
${cell}

`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":262,"value":"md`## Les propriétés statistiques`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":190,"value":"$31","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":264,"value":"md`## Les graphiques`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":44,"value":"svg``","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":88,"value":"style = ({\n width: width / 2 * 0.8,\n height: (width / 2 * 0.8) * 0.5,\n dot: {\n radius: 5,\n fill: 'indianred',\n },\n line: {\n stroke: 'steelblue',\n },\n axis: {\n stroke: 'gray',\n fontSize: width / 90\n }\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":35,"value":"drawGraph = (dataIndex, x, y) => svg`\n\n ${ drawAxisX() }\n ${ drawAxisY() }\n ${ drawRegressionLine(data[dataIndex]) }\n ${ drawDots(data[dataIndex]) }\n \n\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":137,"value":"drawAxisX = () => svg`\n \n ${\n [2,4,6,8,10,12,14,16,18]\n .map(d => svg`\n ${d}\n `)\n }\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":162,"value":"drawAxisY = () => svg`\n \n ${\n [4,6,8,10,12]\n .map(d => svg`\n ${d}\n `)\n }\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":74,"value":"drawRegressionLine = data => {\n const { x1, y1, x2, y2 } = getLinearRegression(data)\n return svg``\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":85,"value":"drawDots = data =>\n data\n .map(([x, y]) => ([xScale(x), yScale(y)]))\n .map(([cx, cy]) => svg``)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":2,"value":"data = [\n [[10,8.04],[8,6.95],[13,7.58],[9,8.81],[11,8.33],[14,9.96],[6,7.24],[4,4.26],[12,10.84],[7,4.82],[5,5.68]],\n [[10,9.14],[8,8.14],[13,8.74],[9,8.77],[11,9.26],[14,8.1],[6,6.13],[4,3.1],[12,9.13],[7,7.26],[5,4.74]],\n [[10,7.46],[8,6.77],[13,12.74],[9,7.11],[11,7.81],[14,8.84],[6,6.08],[4,5.39],[12,8.15],[7,6.42],[5,5.73]],\n [[8,6.58],[8,5.76],[8,7.71],[8,8.84],[8,8.47],[8,7.04],[8,5.25],[19,12.5],[8,5.56],[8,7.91],[8,6.89]]\n]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":13,"value":"xScale = d3.scaleLinear().range([0, style.width]).domain([0, 20])","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":18,"value":"yScale = d3.scaleLinear().range([style.height, 0]).domain([3, 13])","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":69,"value":"getLinearRegression = dataset => {\n const [x1, y1] = regression.linear(dataset).predict(0)\n const [x2, y2] = regression.linear(dataset).predict(20)\n return { x1, y1, x2, y2 }\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":206,"value":"getCorrelation = (x, y) => {\n // https://memory.psych.mun.ca/tech/js/correlation.shtml\n // refactored\n if (x.length !== y.length) { throw new Error('Length of x and y do not match') }\n const length = x.length\n\n const sum = arr => arr.reduce((r, c) => r + c, 0)\n const sum_x = sum(x)\n const sum_y = sum(y)\n const sum_xy = sum(x.map((d, i) => d * y[i]))\n const sum_x2 = sum(x.map(d => d * d))\n const sum_y2 = sum(y.map(d => d * d))\n \n const step1 = (length * sum_xy) - (sum_x * sum_y)\n const step2 = (length * sum_x2) - (sum_x * sum_x)\n const step3 = (length * sum_y2) - (sum_y * sum_y)\n const step4 = Math.sqrt(step2 * step3)\n return step1 / step4\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":8,"value":"d3 = require('d3-scale')","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":61,"value":"regression = require('https://bundle.run/regression@2.0.1')","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":184,"value":"math = require('https://bundle.run/mathjs@5.4.1')","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"}],"files":"$W32","stdlib":"1","titling":"auto"}} 30:"$2f:body"