const rawData = [

    [0, 2.1],

    [1, 2.4],

    [2, 2.6],

    [4, 2.8],

    [5, 3]

];

​

//get regression object

//type of regression is choosen every time manually according to

//experimental data

const result = regression('linear', rawData);

​

//get coefficients from calculated formula

var coeff = result.equation;

​

anychart.onDocumentReady(function () {

​

    var data_1 = rawData;

    var data_2 = setTheoryData(rawData);

​

    chart = anychart.scatter();

​

    chart.title("The calculated formula is " + result.string + "\nThe coefficient of determination (R2) is " + result.r2.toPrecision(2));

​

    chart.legend(true);

​

// create the first series (marker) and set the experimental data

    var series1 = chart.marker(data_1);

    series1.name("Experiment data");

​

// create the second series (line) and set the theoretical data

    var series2 = chart.line(data_2);

    series2.name("Theoretically calculated data");

    series2.markers(true);

​

    chart.container("container");

    chart.draw();

});

​

//helper to input X and calculate Y using founded formula

//suites to any type of regression

function formula(coeff, x) {

    var result = null;

    for (var i = 0, j = coeff.length - 1; i < coeff.length; i++, j--) {

        result += coeff[i] * Math.pow(x, j);

    }

    return result;

}

​

//helper to set theoretical data array of [X][Y]

//using experimental X coordinates

//suites to any type of regression

function setTheoryData(rawData) {

    var theoryData = [];

    for (var i = 0; i < rawData.length; i++) {

        console.log(rawData[i][0] + "    " + formula(coeff, rawData[i][0]));

        theoryData[i] = [rawData[i][0], formula(coeff, rawData[i][0])];

    }

    return theoryData;

}