Description of Individual Course Units
 Course Unit Code Course Unit Title Type of Course Unit Year of Study Semester Number of ECTS Credits İST311 FUZZY PROBABILITY AND STATISTICS Elective 3 5 4
Level of Course Unit
First Cycle
Objectives of the Course
Fuzzy logic models human logic inference systems in a linear and uncomplicated manner. In the course, fundamentals of fuzzy logic are mentioned. Moreover, statistical methods that are developed with the use of fuzzy logic are presented.
Name of Lecturer(s)
Doç. Dr. Ali MERT
Learning Outcomes
 1 To learn the fundamentals of fuzzy logic 2 To learn the difference between fuzzy and classical statistical methods. 3 To learn how fuzzy statistical methods are applied.
Mode of Delivery
Face to Face
Prerequisites and co-requisities
Recommended Optional Programme Components
Course Contents
Fuzzy sets and their statement types. Membership functions and their types. Definition of fuzzy number and its statement types. Operations on fuzzy sets and fuzzy arithmetic. Defuzzification methods. Fuzzy linear programming problem and its solution methods. Systems operating with fuzzy rules. Fuzzy probability theory. Fuzzy random variable and its types. Fuzzy estimators of population parameters. Fuzzy hypotheses test. Fuzzy regression analysis. Recent applications concerning fuzzy systems.
Weekly Detailed Course Contents
 Week Theoretical Practice Laboratory 1 Recent Applications Concerning Fuzzy Systems 2 Fuzzy Sets and Fundamental Definitions 3 Membership Functions and Types of Fuzzy Number. 4 Operations on Fuzzy Set and Fuzzy Arithmetic 5 Defuzzification Strategies. 6 Fuzzy Linear Programming 7 Fuzzy Linear Programming 8 Mid-Term 9 Fuzzy Rule-Based Systems 10 Fuzzy Probability Theory 11 Discrete Fuzzy Random Variables 12 Continuous Fuzzy Random Variables 13 Fuzzy Estimator of Population Parameters 14 Fuzzy Hypotheses Test 15 Fuzzy Hypotheses Test 16 Fuzzy Regression Analysis
J.J. Buckley, Fuzzy Probability and Statistics, Springer – Verlag Berlin, 2006. H.T. Nguyen and B. Wu, Fundamentals of Statistics with Fuzzy Data, Springer – Verlag Berlin, 2006. D. Dubois and H. Prade (edt.), Fundamentals of Fuzzy Sets, Kluwer Academic Publishers, 2000.
Planned Learning Activities and Teaching Methods
Assessment Methods and Criteria
 Term (or Year) Learning Activities Quantity Weight Midterm Examination 1 65 Project Presentation 1 35 SUM 100 End Of Term (or Year) Learning Activities Quantity Weight Final Sınavı 1 100 SUM 100 Term (or Year) Learning Activities 40 End Of Term (or Year) Learning Activities 60 SUM 100
Language of Instruction
Lisan Kodları
Work Placement(s)