Update a prior belief with Bayes' theorem given new evidence, check the result under a normal model, then bound it with a CI.
Update a prior probability given new evidence using Bayes' theorem.
bayes({"prior": 100, "sensitivity": 100, "false_positive": 100})Check the updated probability against a normal distribution model.
normal_prob({"mean": 100, "std_dev": 100, "x": 100})Bound the updated estimate with a confidence interval.
confidence_interval({"mode": "mean", "mean": 100, "std_dev": 100})