code: def confidence_interval_dichotomous(
      point_estimate,
      sample_size,
      confidence=0.95,
      bias=False,
      percentage=True,
      **kwargs,
  ):
      """Dichotomous confidence interval from sample size and maybe a bias"""
      alpha = ppf((confidence + 1) / 2, sample_size - 1)
      p = point_estimate
      if percentage:
          p /= 100
  
      margin = sqrt(p * (1 - p) / sample_size)
      if bias:
          margin += 0.5 / sample_size
      if percentage:
          margin *= 100
  
      return (
          point_estimate - alpha * margin,
          point_estimate + alpha * margin,
      )
  
imports: from math import log, pi, sqrt
label_desc: Use image node_id 5 for calling a global function with example usage: confidence_interval_dichotomous(point_estimate, sample_size, confidence, bias, percentage) and returns: unknown,  unknown