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Course Description Course Name : Decision Analysis Course Code : IEM 758 Course Type : Optional Level of Course : Second Cycle Year of Study : 1 Course Semester : Spring (16 Weeks) ECTS : 6 Name of Lecturer(s) : Asst.Prof.Dr. SEMİN PAKSOY Learning Outcomes of the Course : Analyzes the problems thinking analytically Gains the ability to classify by structuring the elements of decision problems Gains the ability to perform the multiobjective decision making techniques Gains the ability to perform the multiattribute desicion making techniques Mode of Delivery : Face-to-Face Prerequisites and Co-Prerequisites : None Recommended Optional Programme Components : None Aim(s) of Course : The aim of this course is to provide the students with decision making techniques which support the decision making process Course Contents : The course covers decision problems and structures, influence diagrams, decision tree and the calculation of expected values, making a choice and evaluation of information, the benefits and the expected benefit approach, decision making with multiattribute/multiobjective, dominance and multiple attributes, balancing conflicting objectives, AHP and TOPSIS methods Language of Instruction : Turkish Work Place : Classroom   Course Outline /Schedule (Weekly) Planned Learning Activities Week Subject Student's Preliminary Work Learning Activities and Teaching Methods 1 Elements of decision problems Reading relevant parts in source books according to weekly program Lecture, problem solving 2 Structuring decisions Reading relevant parts in source books according to weekly program Lecture, problem solving 3 Decision trees Reading relevant parts in source books according to weekly program Lecture, problem solving 4 Making choices Reading relevant parts in source books according to weekly program Lecture, problem solving 5 Sensitivity analysis Reading relevant parts in source books according to weekly program Lecture, problem solving 6 Decision making Reading relevant parts in source books according to weekly program Lecture, problem solving 7 Modeling uncertainty Reading relevant parts in source books according to weekly program Lecture, problem solving 8 Midterm exam - - 9 Value of information Reading relevant parts in source books according to weekly program Lecture, problem solving 10 Utility theory Reading relevant parts in source books according to weekly program Lecture, problem solving 11 Conflicting objectives and decision making Reading relevant parts in source books according to weekly program Lecture, problem solving 12 Multiattribute decision making Reading relevant parts in source books according to weekly program Lecture, problem solving 13 Analytical hiyerarchy process Reading relevant parts in source books according to weekly program Lecture, problem solving 14 Topsis method Reading relevant parts in source books according to weekly program Lecture, problem solving 15 Decision analysis with spreadsheets Reading relevant parts in source books according to weekly program Computer application 16/17 Final examination - -   Required Course Resources Resource Type Resource Name Recommended Course Material(s)  An Introduction to Management Science: Quantitive Approaches to Decisions Making, David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, Thomson, 2003  Making Hard Decisions: An Intoducting to Decision Analysis, Robert T. Cliemen, Duxbury Press, 1996 Required Course Material(s)  Yönetimde Çok Amaçlı Karar Verme, R. Evren, F. Ülengin, İTÜ  Decisions Making in the Manufacturing Environment, R. Venkata Rao, Springer   Assessment Methods and Assessment Criteria Semester/Year Assessments Number Contribution Percentage     Mid-term Exams (Written, Oral, etc.) 1 80     Homeworks/Projects/Others 10 20 Total 100 Rate of Semester/Year Assessments to Success 40   Final Assessments 100 Rate of Final Assessments to Success 60 Total 100   Contribution of the Course to Key Learning Outcomes # Key Learning Outcome Contribution* 1 Explains Econometric concepts 3 2 Equipped with the foundations of Economics, develops Economic models 4 3 Models problems using the knowledge of Mathematics, Statistics, and Econometrics 4 4 Acquires the ability to analyze, benchmark, evaluate and interpret at conceptual levels to develop solutions to problems 5 5 Collects, edits, and analyzes data 5 6 Uses advanced software packages concerning Econometrics, Statistics, and Operation Research 3 7 Develops the ability to use different resources in an area which has not been studied in the scope of academic rules, synthesizes the information gathered, and gives effective presentations 3 8 Speaks Turkish and at least one other foreign language in accordance with the requirements of academic and business life. 4 9 Questions traditional approaches and their implementation and develops alternative study programs when required 5 10 Recognizes and implements social, scientific, and professional ethic values 1 11 Gives a consistent estimate for the model and analyzes and interprets its results 5 12 Takes responsibility individually and/or as a member of a team; leads a team and works effectively 4 13 Defines the concepts of statistics, operations research and mathematics. 4 14 Knowing the necessity of life-long learning, follows the latest developments in the field of study and improves himself continiously 4 15 Follows the current issues, and interprets the data about economic and social events. 3 16 Understands and interprets the feelings, thoughts and behaviours of people and expresses himself/herself orally and in written form efficiently 5 * Contribution levels are between 0 (not) and 5 (maximum).   Student Workload - ECTS Works Number Time (Hour) Total Workload (Hour) Course Related Works     Class Time (Exam weeks are excluded) 14 3 42     Out of Class Study (Preliminary Work, Practice) 14 4 56 Assesment Related Works     Homeworks, Projects, Others 10 3 30     Mid-term Exams (Written, Oral, etc.) 1 10 10     Final Exam 1 10 10 Total Workload: 148 Total Workload / 25 (h): 5.92 ECTS Credit: 6