Induction, Decision and Game Theory
“If my parents had brought me up in a house where all the coins were 99% heads, what probability should I assign to a coin flip?”
Text: An Introduction to Decision Theory by Martin Peterson
Prof: Dr. Christopher Stephens
Entertaining lecturer. Full of funny examples and jokes. Also willing to go through examples quite slowly to ensure everyone understands.
The course is largely mathematical in nature, and as there are not a lot of pre-requisites the complexity of mathematics is not very high. We do cover a fair deal of diverse content in the course though so you might need to allocate some time to learn the material even if you do not find the mathematics challenging. The midterm average was quite low, and the highest grade was only 92% so it did not turn out to be much of a GPA booster if that was students motivation in taking the course.
Decisions under Ignorance
Decisions under Risk
Interpretations of Probability
Dutch Book Arguments: Need to learn how to set the different cases up correctly. One useful intuition is that you usually want to encourage the victim to bet for what they are over-confident about and against what they are under-confident about.
Bayes Theorem: They sometimes ask Bayes Theorem questions in an odd way, not sure if it is mathematically incorrect or I am just being stupid. The confusion is related to sampling.
Final Paper: Not that used to writing a paper. Spent a great deal of time getting my thesis to be specific.
A decent introduction to Decision and Game Theory that is more nuanced and skeptical than you might get from an Economics or Mathematics class. Would have enjoyed even more emphasis on the philosophical issues and less on the mathematics.