s10-pearson-correlation-coefficient.js

function processData(input) {
  //Enter your code here
  function mean(x, n) {
    return x.reduce((a, b) => a + b) / n
  }

  function covariance(x, y, n) {
    let c = 0,
      mx = mean(x, n),
      my = mean(y, n)

    for (let i = n; i-- > 0;) {
      c += (x[i] - mx) * (y[i] - my)
    }

    c /= n - 1

    return c
  }

  function standardDeviation(x, n) {
    let v = 0,
      m = mean(x, n)

    for (let i = n; i-- > 0;)
      v += Math.pow(x[i] - m, 2)

    v /= n - 1

    return Math.sqrt(v)
  }

  function pearsonCorrelationCoefficient(x, y, n) {
    return covariance(x, y, n) / (standardDeviation(x, n) * standardDeviation(y, n))
  }

  input = input.split('\n')

  let n = parseInt(input[0]),
    x = input[1].split(' ').map(Number),
    y = input[2].split(' ').map(Number)

  console.log(pearsonCorrelationCoefficient(x, y, n).toFixed(3))
}

processData(`10
10 9.8 8 7.8 7.7 7 6 5 4 2
200 44 32 24 22 17 15 12 8 4`)