Jonathan Eckstein's Business Decision Analytics under Uncertainty Classes 33:136:400:01/02
(Fall 2017)

This site is for both Fall 2017 sections of the course.  The Spring 2017 version and earlier versions are also available.

Announcements (As of November 16, 2017 04:58 PM)

Usual Office Hour Schedule

My office is 100 Rockafeller Road, room 5145.   Office hours are tentatively scheduled for

This schedule is subject to change.  Changes will be announced above.  You may also make appointments if regularly scheduled office hours conflict with your class schedule.

Handouts and Class Materials

  1. Wednesday, September 6:  Introduction,  procedures, syllabus, introduction to decision making under uncertainty
  2. Monday, September 11:  Introduction to decision trees, probability review
  3. Wednesday, September 13:   Conditional probability and Bayes' formula
  4. Monday, September 18 (covered by substitute instructor):  More Bayes analysis and decision trees
  5. Wednesday, September 20 (covered by substitute instructor):  More Bayes analysis and decision trees, risk considerations
  6. Monday, September 25:  Critical fractile analysis, including "chunky" demand
  7. Wednesday, September 27:  Critical fractile case study
  8. Monday, October 2:  Introduction to dynamic programming
  9. Wednesday, October 4:  Review for exam
  10. Monday, October 9:  First midterm exam (practice material on Blackboard)
  11. Wednesday, October 11:   More dynamic programming by hand
  12. Monday, October 16:  Review exam results, dynamic programming by spreadsheet, start Python
  13. Wednesday, October 18:  Python refresher/primer
  14. Monday, October 23:  Our first dynamic programming solution in Python (substitute instructor)
  15. Wednesday, October 25:  More deterministic dynamic programming in Python
  16. Monday, October 30:  Introducing stochastic dynamic programming
  17. Wednesday, November 1:  Stochastic programming with shortage penalties or net present value, start elementary stochastic processes
  18. Monday, November 6:  More elementary stochastic processes, using Poisson and binomial distributions within dynamic programming calculations
  19. Wednesday, November 8:  The curse of dimensionality, introduction/refresher on Monte Carlo simulation 
  20. Monday, November 13:  Discuss midterm format, more Monte Carlo simulation
  21. Wednesday, November 15:  Review for exam, start Monte Carlo simulation of queuing systems
  22. Monday, November 20:  Second midterm exam


Homework Solutions

All solutions will be posted on Blackboard and require a password.  Look under "Course documents" and then the "Homework solutions" folder.  The files are in PDF format unless otherwise specified.