code: function standardError(actuals=[], estimates=[]) {
                if (actuals.length !== estimates.length) throw new RangeError('arrays must have the same length');
                const squaredDiff = squaredDifference(actuals, estimates);
                return Math.sqrt((sum(squaredDiff)) / (actuals.length - 2));
              }
docs: The standard error of the estimate is a measure of the accuracy of predictions made with a regression line. Compares the estimate to the actual value
  @memberOf util
  @see {@link http://onlinestatbook.com/2/regression/accuracy.html}
  @example
  const actuals = [ 2, 4, 5, 4, 5, ];
  const estimates = [ 2.8, 3.4, 4, 4.6, 5.2, ];
  const SE = ms.util.standardError(actuals, estimates);
  SE.toFixed(2) // => 0.89
  @param {Number[]} actuals - numerical samples
  @param {Number[]} estimates - estimates values
  @returns {Number} Standard Error of the Estimate