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Course Description Course Name : Simulation Course Code : IEM 762 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. HÜSEYİN GÜLER Learning Outcomes of the Course : Creates the mathematical model of an event. Writes an algorithm to solve the mathematical model with simulation. Codes the written algorithm in a programming language. Defines the consistent Monte carlo estimators of the model parameters. Obtains Monte Carlo estimates for parameters. Chooses virtual samples from the distribution of random variables. 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 the knowledge of simulation that is necessary in statistics and econometrics. It is difficult to solve some problems in these fields analytically. To solve these problems, the simulation method which includes a virtual experiment can be used. In this context, the definition and contents of simulation, techniques used in simulation and mathematical modelling is considered. It is also necessary to use a programming language to simulate an event with a mathematical model. Therefore, the logic behind the alghoritms and MATLAB program is also discussed in the course. Following these topics, Monte Carlo models of some events are investigated to gain practice for students. Course Contents : The course covers random number generators, inverse transform method, simulation in some discrete and continuous distributions, virtual experiment, Monte Carlo estimation, Monte Carlo estimates for moments, Monte Carlo integration, estimating probabilities with Monte Carlo, estimating the size and power of a test, finding critical values with Monte Carlo, simulation in regression models, simulation in time series, the bootstrap method. Language of Instruction : Turkish Work Place : Department of Econometrics, meeting room   Course Outline /Schedule (Weekly) Planned Learning Activities Week Subject Student's Preliminary Work Learning Activities and Teaching Methods 1 Basic concepts, a review of probability and random variables A review of probability and random variables from some reference books Lecture, discussion 2 Probability-integral transformation and random number generators Lecture notes, reference books, Yahoo Group Lecture,discussion, online material 3 Inverse transformation method, simulation in some discrete and continuous distributions Lecture notes, reference books, Yahoo Group Lecture, discussion, computer applications, online material 4 Simulation in some discrete and continuous distributions Lecture notes, reference books, Yahoo Group Lecture, discussion, computer applications, online material 5 Virtual experiment, Monte Carlo estimation Lecture notes, reference books, Yahoo Group, Paper: Usta, Cirak ve Hileli Zar Lecture, discussion, computer applications, experiment, online material 6 Monte Carlo estimates of moments Lecture notes, reference books, Yahoo Group Lecture, discussion, computer applications, homework presentation, online material 7 Monte Carlo integration Lecture notes, reference books, Yahoo Group Lecture, discussion, computer applications, homework presentation, online material 8 Midterm exam A review for the exam 9 Estimating probabilities with Monte Carlo experiment Lecture notes, reference books, Yahoo Group Lecture, discussion, computer applications, homework presentation, online material 10 Monte Carlo estimate of the parameter pi Lecture notes, reference books, Yahoo Group Lecture, discussion, computer applications, homework presentation, online material 11 Estimate of the size and power of a test Lecture notes, reference books, Yahoo Group Lecture, discussion, computer applications, homework presentation, online material 12 Finding critical values with Monte Carlo method Lecture notes, reference books, Yahoo Group Lecture, discussion, computer applications, homework presentation, online material 13 Simulation in a regression model Lecture notes, reference books, Yahoo Group Lecture, discussion, computer applications, homework presentation, online material 14 Simulation in time series Lecture notes, reference books, Yahoo Group Lecture, discussion, computer applications, homework presentation, online material 15 Bootstrapping Lecture notes, reference books, Yahoo Group Lecture, discussion, computer applications, homework presentation, online material 16/17 Final Exam A review for the exam   Required Course Resources Resource Type Resource Name Recommended Course Material(s)  Statistical Simulation, Lecture Notes, Huseyin GULER, Adana, 2006.  An Introduction to the Bootstrap, B. Efron ve R.J. Tibshirani, Chapman & Hall, 1993.  Matematiksel Modelleme ve Simülasyon, Fikri ÖZTÜRK, Levent ÖZBEK, Gazi Kitabevi, Ankara, 2004.  A Course in Simulation, Sheldon M. Ross, Macmillan, New York, 1990.  Simulation Modelling & Analysis, A. Law ve W. Kelton, McGraw-Hill, 1991.  Simulation: A Statistical Perspective, J. P.C. Kleijnen ve W. van Groenendaal, John Wiley, 1992. Required Course Material(s)  Yahoo group created for the course  "Usta, Cirak ve Hileli Zar", Huseyin Guler, n´den N´ye Gezinti, Sayi 1, Temmuz-Agustos 2011, s.14.   Assessment Methods and Assessment Criteria Semester/Year Assessments Number Contribution Percentage     Mid-term Exams (Written, Oral, etc.) 1 50     Homeworks/Projects/Others 5 50 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 4 2 Equipped with the foundations of Economics, develops Economic models 0 3 Models problems using the knowledge of Mathematics, Statistics, and Econometrics 5 4 Acquires the ability to analyze, benchmark, evaluate and interpret at conceptual levels to develop solutions to problems 4 5 Collects, edits, and analyzes data 1 6 Uses advanced software packages concerning Econometrics, Statistics, and Operation Research 5 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 4 8 Speaks Turkish and at least one other foreign language in accordance with the requirements of academic and business life. 1 9 Questions traditional approaches and their implementation and develops alternative study programs when required 3 10 Recognizes and implements social, scientific, and professional ethic values 0 11 Gives a consistent estimate for the model and analyzes and interprets its results 2 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. 5 14 Knowing the necessity of life-long learning, follows the latest developments in the field of study and improves himself continiously 1 15 Follows the current issues, and interprets the data about economic and social events. 0 16 Understands and interprets the feelings, thoughts and behaviours of people and expresses himself/herself orally and in written form efficiently 1 * 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 5 70 Assesment Related Works     Homeworks, Projects, Others 5 5 25     Mid-term Exams (Written, Oral, etc.) 1 10 10     Final Exam 1 10 10 Total Workload: 157 Total Workload / 25 (h): 6.28 ECTS Credit: 6