31:T589,{ const svgDims = [600,400] const svg = d3.select(DOM.svg(svgDims[0],svgDims[1])).attr("style","background:white;border:1px solid white") const xScale = d3.scaleLinear().domain([-350,350]).range([30,570]) const yScale = d3.scaleLinear().domain([-5,120]).range([370,30]) const xAxis = svg.append("g").attr("transform",`translate(0,${yScale(0)})`).call(d3.axisBottom(xScale)) const yAxis = svg.append("g").attr("transform",`translate(${xScale(0)},0)`).call(d3.axisLeft(yScale)) for(let i = 0; i < 390; i++){ svg.append("circle") .attr("r",3) .attr("cx",xScale(train[i].Diff)) .attr("cy",yScale(train[i].W)) } const regress = ss.linearRegression(train.map(d => [d.Diff,parseInt(d.W)])) const estSlope = regress.m const estInt = regress.b if(method == "1"){ mutable m = slope mutable b = intercept }else{ mutable m = estSlope mutable b = estInt } const pathData = d3.line().x(d => xScale(d.x)).y(d => yScale(m*d.x+ b))(linePoints) const path = svg.append("path") .attr("d",pathData) .attr("stroke","cornflowerblue") .attr("stroke-width",3) .attr("fill","none") let sumSquares = 0 for(let i = 0; i < 390; i++){ const y = train[i].W const yhat = m*train[i].Diff + b const squaredDiff = Math.pow(y - yhat,2) sumSquares += squaredDiff } mutable rmse = Math.sqrt(sumSquares/390) yield svg.node() }32:T51d,{ const svgDims = [600,400] const svg = d3.select(DOM.svg(svgDims[0],svgDims[1])).attr("style","background:white;border:1px solid white") const xScale = d3.scaleLinear().domain([-350,350]).range([30,570]) const yScale = d3.scaleLinear().domain([-5,120]).range([370,30]) const xAxis = svg.append("g").attr("transform",`translate(0,${yScale(0)})`).call(d3.axisBottom(xScale)) const yAxis = svg.append("g").attr("transform",`translate(${xScale(0)},0)`).call(d3.axisLeft(yScale)) for(let i = 0; i < 180; i++){ svg.append("circle") .attr("r",3) .attr("cx",xScale(test[i].Diff)) .attr("cy",yScale(test[i].W)) } const regress = ss.linearRegression(train.map(d => [d.Diff,parseInt(d.W)])) const estSlope = regress.m const estInt = regress.b const pathData = d3.line().x(d => xScale(d.x)).y(d => yScale(estSlope*d.x+ estInt))(linePoints) const path = svg.append("path") .attr("d",pathData) .attr("stroke","cornflowerblue") .attr("stroke-width",3) .attr("fill","none") let sumSquares = 0 for(let i = 0; i < 180; i++){ const y = test[i].W const yhat = estSlope*test[i].Diff + estInt const squaredDiff = Math.pow(y - yhat,2) sumSquares += squaredDiff } mutable rmseTest = Math.sqrt(sumSquares/180) yield svg.node() }33:[] 2f:{"title":"Predicting Wins in Baseball","cells":[{"id":0,"value":"md`# Predicting Wins in Baseball`","pinned":false,"hidden":false,"mode":"ojs"},{"id":54,"value":"html`

Data Wrangling

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":23,"value":"data = d3.csv(`https://gist.githubusercontent.com/bendazz/c36e23b3400ba346107eefdcb9e48b0f/raw/1e69dab04fd605be0fcadc1953f3c5dfa1e3091c/Teams.csv`)","pinned":false,"hidden":false,"mode":"ojs"},{"id":28,"value":"dataExtract = data.filter(d => d.yearID >= 2000)\n.map(d => ({yearID:d.yearID,W:d.W,R:d.R,RA:d.RA}))","pinned":false,"hidden":false,"mode":"ojs"},{"id":31,"value":"dataManip = dataExtract.map(d => ({yearID:d.yearID,W:d.W,Diff:d.R - d.RA}))","pinned":false,"hidden":false,"mode":"ojs"},{"id":50,"value":"train = dataManip.filter(d => d.yearID < 2013)","pinned":false,"hidden":false,"mode":"ojs"},{"id":38,"value":"test = dataManip.filter(d => d.yearID >= 2013)","pinned":false,"hidden":false,"mode":"ojs"},{"id":62,"value":"html`

Estimation

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":108,"value":"tex`y = ${d3.format(\".2f\")(m)}x + ${d3.format(\".2f\")(b)}`","pinned":false,"hidden":false,"mode":"ojs"},{"id":118,"value":"tex`rmse = ${d3.format(\".2f\")(rmse)}`","pinned":false,"hidden":false,"mode":"ojs"},{"id":67,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":94,"value":"viewof intercept = slider({max:120,description:\"set intercept\"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":100,"value":"viewof slope = slider({max:.5,description:\"set slope\"})","pinned":false,"hidden":false,"mode":"ojs"},{"id":122,"value":"viewof method = radio({options:[\n {label:\"visual best\",value:1},\n {label:\"mathematical best\",value:2}\n],value:1})","pinned":false,"hidden":false,"mode":"ojs"},{"id":164,"value":"html`

Prediction

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":167,"value":"viewof n = number({value:0,step:1})","pinned":false,"hidden":false,"mode":"ojs"},{"id":170,"value":"tex`y = ${0.10}*\\color{tomato}${n}\\color{black} + ${80.96} = \\color{tomato}${.1*n+80.96}`","pinned":false,"hidden":false,"mode":"ojs"},{"id":180,"value":"html`

Testing

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":192,"value":"tex`y = ${0.10}x + ${80.96}`","pinned":false,"hidden":false,"mode":"ojs"},{"id":197,"value":"tex`rmse = ${d3.format(\".2f\")(rmseTest)}`","pinned":false,"hidden":false,"mode":"ojs"},{"id":185,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":84,"value":"html`

Variables and Code

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":87,"value":"linePoints = {\n const data = []\n for(let i = -350;i <= 350; i++){\n data.push({x:i,y:slope*i+intercept})\n }\n return data\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":111,"value":"mutable rmse = 0","pinned":false,"hidden":false,"mode":"ojs"},{"id":186,"value":"mutable rmseTest = 0","pinned":false,"hidden":false,"mode":"ojs"},{"id":155,"value":"mutable m = 0","pinned":false,"hidden":false,"mode":"ojs"},{"id":157,"value":"mutable b = 0","pinned":false,"hidden":false,"mode":"ojs"},{"id":5,"value":"html`

Libraries

`","pinned":false,"hidden":false,"mode":"ojs"},{"id":7,"value":"import {slider,button,select,text,radio,checkbox,number} from \"@jashkenas/inputs\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":8,"value":"d3 = require(\"d3@5\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":10,"value":"stdlib = require( \"https://unpkg.com/@stdlib/stdlib@0.0.32/dist/stdlib-flat.min.js\" )","pinned":false,"hidden":false,"mode":"ojs"},{"id":13,"value":"normal = stdlib.base.random.normal","pinned":false,"hidden":false,"mode":"ojs"},{"id":15,"value":"ss = require(\"https://unpkg.com/simple-statistics@6.1.0/dist/simple-statistics.min.js\")","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W33","stdlib":"1","titling":"auto"}