Course home page (Spring 2016)
Teachers: Prof. Jeffrey Keisler and Prof. Ahti Salo
Course assistant: Dr. Eeva Vilkkumaa
Why this course?
Decisions about how to best allocate scarce resources among different courses of actions are prevalent across a broad spectrum of techno-economic planning problems, such as energy investments and capital budgeting. Such decisions can be supported by methods of Portfolio Decision Analysis (PDA). This course provides a review of recent literature in PDA. On the course, the student will learn about
- Novel PDA methodologies that can be used to carry out innovative action research and solve decision problems in the student's own field, and
- The research process (e.g., selecting publication outlets, writing reviews, and responding to reviewers).
This course is open to students planning to pursue doctoral work in systems analysis or related areas, and who have completed at least one semester of their graduate course work.
Course content
Each class will include student-led discussions of 1-2 recent PDA articles and a group discussion about some aspect of the research process. Each student will work with a partner to prepare the discussion for one journal article. This will involve submitting a 1500 word report and giving a 10-15 minute presentation about the paper in a predetermined format. All students will be expected to review (though not analyze) the article(s) to be discussed each class and to prepare a list of 3-4 questions or discussion points prior to class, and to participate in class discussion.
Practical matters
Teaching: Seven teaching modules (7 x 2h = 14h) during 22.2-23.3.
Assessment
mehtods: Students will be assessed based on the written report about their selected article (30%), the presentation and discussion of the article (30%), consistent preparation of questions and discussion points about other articles (30%), and participation in the article discussions and group discussions (10%).
Grading scale: Pass / fail
Study
material: Powerpoint slides, handouts, and articles.
Language of instruction: English
Prerequisites: Familiarity with decision analysis, comfort with mathematical notation and basic concepts in probability.