code: function(zCriticalValue) {
          var squaredZCriticalValue = zCriticalValue * zCriticalValue;
          var adjustedNumTrials = this.numTrials + squaredZCriticalValue;
          var adjustedBinomial = new Abba.BinomialDistribution(
              adjustedNumTrials,
              (this.numSuccesses + squaredZCriticalValue / 2) / adjustedNumTrials);
          return new Abba.ValueWithError(
              adjustedBinomial.probability,
              adjustedBinomial.standardDeviation / adjustedBinomial.numTrials);
      }
docs: /* Compute an estimate of the underlying probability of success.
  
  Uses the "Agresti-Coull" or "adjusted Wald" interval, which can be thought of as a Wald
  interval with (zCriticalValue^2 / 2) added to the number of successes and the number of
  failures. The estimated probability of success is the center of the interval. This provides
  much better coverage than the Wald interval (and many other intervals), though it has the
  unintuitive property that the estimated probabilty is not numSuccesses / numTrials. See
  (section 1.4.2 and problem 1.24):
  
  Agresti, Alan. Categorical data analysis. New York, NY: John Wiley & Sons; 2002.
  
  An ordinary Wald interval can be obtained by passing zCriticalValue = 0.