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Managerial Decision Making Session-By-Session Outline

Week 3  

Link to Week 3 Survey on Streak (Serial Correlation) Probabilities

Week 3 Slides Representativeness

Week 3 Slides Representativeness and Availability

Week 3 Writing Assignment Options:

(At least one of the Writing Assignments for Weeks 2 or 3 must be chosen, due at the beginning of class) Remember that you must turn in 4 assignments over the course of the next 8 weeks.    

Try to keep to 700 words (there are 2 options you may choose from this week. Submit ONLY your Tuck ID, not your name, and please copy the question below at the top of the paper that you turn in):

Option 1: You have been chosen the Decision Making czar within your organization. Bayes Rule and the more general idea of Bayesian updating are a mathematical formula and big-picture concept for the "correct" use of aggregating new data with old opinions. Explain it thoroughly in qualitative terms, and give an example (numerical or qualitative) that has not been covered in class, where answers using Bayes Rule and human intuition are very different. Focus on the following: What prescriptive Bayesian measures can you recommend to improve the quality of your firm's decisions? Are there limitations to the Bayesian model?

Option 2: The academically well-accepted notion of rationality claims that people's decisions should be frame invariant. In the real world, however, many managerial and political decisions would have been made very differently if decision makers had considered the problem from different but effectively equivalent perspectives.

a) Describe a situation, in an organization you worked or are working for, or a fictitious organization, where framing led to a poor decision.
b) Discuss the competing frames that the key decision makers could have used to improve upon the decision choice that was made.
c) What organizational fixes should you recommend in the future to help decision makers reach better decisions, ones in the best interest of the organization.

Session 5: April 7 Heuristics (1) - Representativeness

Topics:
" The conjunction Fallacy
" Base Rates and Regression to the Mean
" The Fallacy of Intervention
" Overuse of Causal Data
" The Hot Hand
" Local Representativeness

AFTER-class Readings:
**** Kahneman and Tversky, Extentional Versus Intuitive Reasoning: The Conjunction Fallacy In Probability Judgment, CP 5-1
**** Kahneman and Tversky, Subjective Probability: A Judgment of Representativeness, CP 5-2

Session 6: April 8 Heuristics (2) - Availability

Topics:
" Sample and Storage Biases
" Vividness
" Simpson's Paradox

AFTER-class Readings:
**** Kahneman and Tversky, Availability: A Heuristic for Judging Frequency and Probability, CP 6-1

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