Graduate Studies Reports Access

Graduate Course Proposal Form Submission Detail - EIN6353
Tracking Number - 2472

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Current Status: Approved, Permanent Archive - 2011-06-30
Campus: Tampa
Submission Type: New
Course Change Information (for course changes only):
Comments: to GC for review 4/4/11; approved 4/18/11. to USF System for concurrence 5/3/11; ready for SCNS 5/11/11. submit as 6010, nmbr appd 6353. SCNS approved effective 5/1/11. posted in banner


Detail Information

  1. Date & Time Submitted: 2011-02-21
  2. Department: Industrial and Management Systems Engineering
  3. College: EN
  4. Budget Account Number: 210300
  5. Contact Person: Dr. Alex Savachkin
  6. Phone: 8139745577
  7. Email: alexs@usf.edu
  8. Prefix: EIN
  9. Number: 6353
  10. Full Title: Risk and Decision Analysis
  11. Credit Hours: 3
  12. Section Type: C - Class Lecture (Primarily)
  13. Is the course title variable?: N
  14. Is a permit required for registration?: Y
  15. Are the credit hours variable?: N
  16. Is this course repeatable?:
  17. If repeatable, how many times?: 0
  18. Abbreviated Title (30 characters maximum): Risk and Decision Analysis
  19. Course Online?: C - Face-to-face (0% online)
  20. Percentage Online: 0
  21. Grading Option: R - Regular
  22. Prerequisites:
  23. Corequisites:
  24. Course Description: This course gives a formal introduction to risk analysis and utility theory. It focuses on the conceptual and mathematical foundations underlying the quantification and management of risk to support dynamic decision making under uncertainty.

  25. Please briefly explain why it is necessary and/or desirable to add this course: Needed to compete with national trends
  26. What is the need or demand for this course? (Indicate if this course is part of a required sequence in the major.) What other programs would this course service? The course will address an important need to foster a cadre of professionals equipped with an ability to provide intelligent decision support in dynamic and uncertain environments.
  27. Has this course been offered as Selected Topics/Experimental Topics course? If yes, how many times? Yes, 2 times
  28. What qualifications for training and/or experience are necessary to teach this course? (List minimum qualifications for the instructor.) A Ph.D. in industrial engineering or operations research.
  29. Objectives: To get exposed to the theory of decision making under uncertainty and risk and build foundations for its application in engineering, healthcare, and finances.
  30. Learning Outcomes: The students will develop an understanding of the main quantitative principles underlying modern decision theory and risk analysis.
  31. Major Topics: 1. Dynamic probabilistic systems

    2. Stochastic dynamic optimization

    3. Decision making under strict uncertainty

    4. Decision making under risk

    5. Utility theory

    6. Risk attitudes

  32. Textbooks: Decisions with Multiple Objectives, R. L. Keeney and H. Raiffa, Cambridge University Press
  33. Course Readings, Online Resources, and Other Purchases: 1. Introduction to Statistical Decision Theory, J. W. Pratt et al.

    2. Decisions under Uncertainty, I. Jordaan.

    3. Dynamic Programming: Models and Applications, E. V. Denardo.

  34. Student Expectations/Requirements and Grading Policy: Grading Policy: Quizzes - 25%; Midterm I, II, III - 25% each.
  35. Assignments, Exams and Tests: Course assessment will consists of multiple quizzes and three midterm exams.
  36. Attendance Policy: Course Attendance at First Class Meeting Policy for Graduate Students: For structured courses, 6000 and above, the College/Campus Dean will set the first-day class attendance requirement. Check with the College for specific information. This policy is not applicable to courses in the following categories: Educational Outreach, Open University (TV), FEEDS Program, Community Experiential Learning (CEL), Cooperative Education Training, and courses that do not have regularly scheduled meeting days/times (such as, directed reading/research or study, individual research, thesis, dissertation, internship, practica, etc.). Students are responsible for dropping undesired courses in these categories by the 5th day of classes to avoid fee liability and academic penalty. (See USF Regulation Registration - 4.0101,

    http://usfweb2.usf.edu/usfgc/ogc%20web/currentreg.htm)

    Attendance Policy for the Observance of Religious Days by Students: In accordance with Sections 1006.53 and 1001.74(10)(g) Florida Statutes and Board of Governors Regulation 6C-6.0115, the University of South Florida (University/USF) has established the following policy regarding religious observances: (http://usfweb2.usf.edu/usfgc/gc_pp/acadaf/gc10-045.htm)

    In the event of an emergency, it may be necessary for USF to suspend normal operations. During this time, USF may opt to continue delivery of instruction through methods that include but are not limited to: Blackboard, Elluminate, Skype, and email messaging and/or an alternate schedule. Its the responsibility of the student to monitor Blackboard site for each class for course specific communication, and the main USF, College, and department websites, emails, and MoBull messages for important general information.

  37. Policy on Make-up Work: Academic misconduct will not be tolerated; violations of academic honesty will be dispatched in accordance with the University policy.
  38. Program This Course Supports: Ph.D. in Industrial Engineering
  39. Course Concurrence Information: The course will cater to the needs of doctoral students from other engineering disciplines as well as students majoring in finance and health care management.


- if you have questions about any of these fields, please contact chinescobb@grad.usf.edu or joe@grad.usf.edu.