# Probability models and human judgement

Establishes mathematical standards before considering judgements and selection effects.

1. [Lecture 1: Probability Models and Axioms](https://ocw.mit.edu/courses/6-041-probabilistic-systems-analysis-and-applied-probability-fall-2010/resources/lecture-1-probability-models-and-axioms/)
   Begin with the rules and objects of a probability model so that later comparisons have an explicit standard.
   Task: Make a sample space for a fictional draw from a box. State what the model assumes about the draw and what it leaves out.

2. [Lecture 2: Conditioning and Bayes' Rule](https://ocw.mit.edu/courses/6-041-probabilistic-systems-analysis-and-applied-probability-fall-2010/resources/lecture-2-conditioning-and-bayes-rule/)
   Conditioning adds information to that model rather than replacing the model with an intuitive story.
   Task: Make a table of counts for two colours and a noisy label. Calculate the colour probability after observing the label; then change the base rate.

3. [Lecture 3: Independence](https://ocw.mit.edu/courses/6-041-probabilistic-systems-analysis-and-applied-probability-fall-2010/resources/lecture-3-independence/)
   Independence is a distinct assumption, often hidden in informal probability arguments.
   Task: Write what independence would mean for two events in your example. Identify a plausible change to the draw that would make the assumption fail.

4. [Lecture 13: Thinking](https://ocw.mit.edu/courses/9-00sc-introduction-to-psychology-fall-2011/resources/lecture-13-thinking/)
   With a comparison rule available, examine human problem solving, heuristics and framing.
   Task: Choose a puzzle and state the intended rule, the information provided and the response. Explain which claimed error actually follows from those premises.

5. [Lecture 4 - Parts of the Soul II](https://oyc.yale.edu/philosophy/phil-181/lecture-4)
   Gendler adds sampling and philosophical questions, showing why a description of reasoning needs more than a list of bias names.
   Task: Distinguish a sampling problem from a disagreement over values. Give one example of each and identify what would resolve it.

6. [Lecture 24 - Asymmetric Information: Auctions and the Winner's Curse](https://oyc.yale.edu/economics/econ-159/lecture-24)
   The auction example applies conditioning to selection: learning that one won can itself be informative.
   Task: Describe what the event of winning reveals in the lecture’s model. State one changed assumption under which the inference would differ; do not turn the exercise into bidding advice.

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