Statistics (mean, variance, standard deviation, ...)

statistics.js

function sum(arr) {
  return arr.reduce((acm, cur) => acm + cur, 0);
}

function mean(xs, correction) {
  var correction = correction || 0;
  var total = xs.length - correction;
  return sum(xs) / total;
}

function dispersion(xs, correction) {
  var m = mean(xs);
  var sq_devs = xs.map(x => Math.pow(x - m, 2));
  return mean(sq_devs, correction);
}

function sd(xs, correction) {
  return Math.sqrt(dispersion(xs, correction));
}

function z_score(x, m, sd) {
  return (x - m) / sd;
}

// Usage
// -----
// raw data
var x_str = '1 5 2 7 1 9 3 8 5 9';

// processed, numerical data
var xs = x_str.split(' ').map(x => parseInt(x));

console.log(sd(xs, 1));

statistics.py

import math


def mean(A):
  """Calculate the mean of A."""
  size = len(A)
  if size <= 0:
    raise TypeError('Cannot take the mean of an empty sample.')
  return sum(A) / size


def variance(A, correction=False):
  """Calculate the variance of A."""
  m, size = mean(A), len(A)
  diff_sq = [(x - m) ** 2 for x in A]
  return sum(diff_sq) / (size - int(correction))


def std(A, correction=False):
  """Calculate the standard deviation of A."""
  return math.sqrt(variance(A, correction))