Big Decisions: Rational Belief and Action in an Uncertain World
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Upon completion of this subject, the student should be able to:
- Identify, relevant to the problem at hand, what does or does not constitute evidence and when facts are incomplete or uncertain.
- Combine evidence from multiple sources, including the beliefs of others, and reason by quantifying those prior beliefs, updating them according to available evidence.
- Decide on the relevant merits of different courses of action and communicate the evidentiary basis and rational methodology underpinning beliefs and decisions
- Prior knowledges and base rates
- Evidence and likelihood
- Converging beliefs and relative hypotheses
- Betting odds and maximising payoffs
- Relative payoffs and risk
- Bayes revisited and the adaptive toolbox
- Prediction versus belief
- Biased sampling
- Rational thinking in the extremes
You should not enrol in this subject if you have successfully completed any of the following subject(s) because they are considered academically equivalent:
- TAS-XBR111-Big Decisions! Rational Belief and Action in an Uncertain World (No longer available)
No additional requirements
In the modern world we must often make decisions under uncertainty, weighing up our options in the face of incomplete (and often conflicting) information. In this subject we examine the problems of evaluating evidence, forming beliefs, and making decisions based on those beliefs. We do this through the lens of Bayesianism, an intuitive view of the world that considers all beliefs and evidence to have some level of uncertainty and subjectivity.
As both a philosophical approach and an explicit mathematical system, Bayesianism is increasingly being used in real world problems across many fields. Using Bayesian approaches to deal with uncertainty is becoming essential to not only the physical and social sciences, but also to applied disciplines such as economics, marketing, law, engineering, IT, medicine and nursing. For example, what should we believe about our health based on the result of a medical test, and what treatment option, if any, should we choose? How should we evaluate evidence for climate change and what policies should we support to deal with its potential consequences? Through a Bayesian approach we can use simple arithmetic to quantify our uncertainty about the evidence, update our beliefs from that evidence, and decide on a course of action - even when there may be no single or "right" course of action.
By understanding the components of Bayesian inference, along with applications of Bayes rule to real world problems, we help students to
think more deeply about how they make decisions, why they make the decisions they do, and ultimately how to make better decisions.
- x2 Quizzes (60%)
- Portfolio (40%)
Current study term: 11 Jul 21 to 17 Oct 21
Check the learning management system (LMS) of your university for textbook details.