COURSE UNIT TITLE

: STATISTICAL SIMULATION

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
STA 5088 STATISTICAL SIMULATION ELECTIVE 3 0 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR EMEL KURUOĞLU KANDEMIR

Offered to

Statistics (English)
STATISTICS (ENGLISH)
Statistics (English)

Course Objective

The course covers simulation modeling and programming in scientific computer programming languages. Proper design and analysis of the simulation experiment is emphasized. The course prepares students to analyze systems using simulation and to employ simulation in their statistical research. Topics include probabilistic aspects of simulation experiments, statistical methodology for designing simulations and interpreting their output, random variate and process generation, and efficiency improvement techniques. At the end of the course students should be able to simulate random data using MATLAB, R etc. programs.

Learning Outcomes of the Course Unit

1   An understanding of fundamental ideas of statistical simulation,
2   Carry out statistical simulation with the use of the programming languages,
3   Produce random numbers in the programming languages,
4   An understanding of advanced structure of statistical programming,
5   Develop the students analytical abilities and ability to present and criticize arguments.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Fundamental Topics in Simulation and Statistical Simulation Methods and Models Fundamental Simulation Concepts
2 Introduction to MATLAB and R
3 Data Types, Manipulation of Data, Operators, Functions
4 Random Variables Discrete and Continues Distributions Modelling Basic Statistics MATLAB and R Applications - Assignment 1
5 Random Number Generators Generating Discrete Random Variables The Inverse Transform Method MATLAB and R Applications - Assignment 2
6 Generating Continues Random Variables The Inverse Transform Method MATLAB and R Applications
7 Generating Continues Random Variables The Rejection Method MATLAB and R Applications - Assignment 3
8 Mid-term
9 Programming Simulations Simulation using a Simulation software (Example, ARENA, GPSS, Simulink etc.)
10 Statistical Validation Techniques Evaluating System Performance MATLAB and R projects for Statistical Computing - Assignment 4
11 Selected Student Simulations
12 Conducting Statistical Studies Project Presentations
13 Conducting Statistical Studies
14 Conducting Statistical Studies

Recomended or Required Reading

Textbook:
Sheldon M. Ross, Simulation, 3rd Ed., Academic Press, 2002.

Supplementary Book:
Averal M. Law and W. David Kelton, Simulation Modeling and Analysis, 3rd Edition, McGraw-Hill, 2000, ISBN: 0070592926.

Planned Learning Activities and Teaching Methods

The course consists of lecture and homework.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 ASG ASSIGNMENT
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE MTE * 0.30 + ASG * 0.40 + FIN * 0.30
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + MAKRASG * 0.40 + MAKRRST * 0.30


Further Notes About Assessment Methods

None

Assessment Criteria

Evaluation of exams, presentation and homework.

Language of Instruction

English

Course Policies and Rules

Attendance to at least 70% for the lectures is an essential requirement of this course and is the responsibility of the student. It is necessary that attendance to the lecture and homework delivery must be on time. Any unethical behavior that occurs either in presentations or in exams will be dealt with as outlined in school policy. You can find the graduate policy at http://web.fbe.deu.edu.tr

Contact Details for the Lecturer(s)

Assist.Prof.Dr.Emel KURUOĞLU
e-posta: emel.kuruoglu@deu.edu.tr
Tel: 0232 301 95 10

Office Hours

Will be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Preparation for final exam 1 48 48
Preparations before/after weekly lectures 12 1 12
Preparation for midterm exam 1 48 48
Preparing assignments 4 9 36
Midterm 1 2 2
Final 1 2 2
TOTAL WORKLOAD (hours) 190

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.134
LO.225444
LO.3444
LO.444
LO.5444

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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