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We will study managerially relevant operations and supply chain problems using the lens of decision-making under uncertainty. There are two steps:

  1. Modeling the uncertainty.
  2. Modeling the tradeoffs in decision-making.

Our primary goal while modeling uncertainty is to come up with a “reasonably good” distribution of the uncertain variable. You may have already studied these ideas in your Core Statistics course. We will borrow these ideas in our course.

I will use R to illustrate these ideas using real data. While you can accomplish these tasks using Excel, it would be in your interest to learn a programming language (such as R/Python) and SQL early on. I am an avid R user; I am happy to help you, should you want to learn R.

I list some resources for learning R and Excel below; there are plenty of resources online.

  • R and R Studio: The best part of R is that it’s free (and relatively user-friendly). Plenty of resources to learn R are available online. Some of my favorite resources are:

    – Classic Reference: R for Data Science

    – Courses from Other Institutions: Grant McDermott, Jenny Bryan.

  • Microsoft Excel/Any Spreadsheet Software: Obtain free license to Office 365 from ASU UTO.

Please let me know if you use any other resource; I would love to include it. Feel free to use any other software as need be.

I plan to use Gurobi in SCM 551 (in R, of course) – I will comment on this at a later stage.