Decision Analysis Sequence

byVaniver8y21st Dec 20116 comments


This is the introduction (conclusion) to my decision analysis sequence. It covers (much more quickly and less completely) what you would expect to see in a semester-long course on decision making. The posts are:

  1. Uncertainty: the basics of treating uncertainties as probabilities and doing Bayesian math.
  2. 5 Axioms of Decision Making: the five steps / assumptions that form the foundation of careful decision-making.
  3. Compressing Reality to Math: how to take a sticky, complicated situation and condense it down to something a calculator can solve, without feeling like you've left something important out.
  4. Measures, Risk, Death, and War: how to deal with many similar prospects (utilities), risks of death, and adversaries.
  5. Value of Information: Four Examples: how to value information-gathering activity, like tests or waiting, and incorporate it into your decision-making process.

I'd like to welcome any comments about the sequence here. What parts did I do well? What parts need work? What parts would you like to see expanded (or removed)?

One of the difficulties in posting about a topic like this is that it's foundational: basic, but important to get right. The idea of an expected utility calculation is not new (although the approach I take here may be novel for many of you) and, like I say in the VoI post, there's often more benefit in applying the process to examples than repeatedly talking about the process. The case studies I have access to, though, are not ones I can publish online, and I don't think I can construct an example that would work as well as a real one. Do people have problems they would like me to analyze with this framework as examples?