Eskisehir Technical University Info Package Eskisehir Technical University Info Package
  • Info on the Institution
  • Info on Degree Programmes
  • Info for Students
  • Turkish
    • Turkish Turkish
    • English English
About the Program Educational Objectives Key Learning Outcomes Course Structure Diagram with Credits Field Qualifications Matrix of Course& Program Qualifications Matrix of Program Outcomes&Field Qualifications
  • Graduate School of Sciences
  • Department of Industrial Engineering
  • Master of Arts (MA) Degree
  • Course Structure Diagram with Credits
  • Stochastic Processes
  • Description
  • Description
  • Learning Outcomes
  • Course's Contribution to Prog.
  • Learning Outcomes & Program Qualifications

Course Introduction Information

Code - Course Title İST522 - Stochastic Processes
Course Type Required Courses
Language of Instruction Türkçe
Laboratory + Practice 3+0
ECTS 7.5
Course Instructor(s)
Mode of Delivery The mode of delivery of this course is face to face
Prerequisites Probability theory
Courses Recomended
Recommended Reading List I. Gikhman, A. Skorokhod (1996) , Introduction to the theory of random processes, Dover Publications.,S. Ghahramani, (2005)Fundamentals of probability with stochastic processes, Third Edition, Prentice Hall.
Assessment methods and criteria 1st Midterm (written examination consisting of open ended problems): 25 %homework (written): 10%project: 25%Final (written examination consisting of open ended problems ): 40%
Work Placement Not Applicable
Sustainability Development Goals

Content

Weeks Topics
Week - 1 Multi-Dimensional Stochastic Variables.
Week - 2 Expected Value of Random Variables
Week - 3 Moment Generating Functions.
Week - 4 Characteristic Functions.
Week - 5 Limit theorems in probability theory.
Week - 6 Conditional probability and conditional distribution functions.
Week - 7 Random Sums and Laplace Transformations of probability distrubutions.
Week - 8 Stochastic processes. Markov chains with discrete parameter and continuous parameter.
Week - 9 Transition probabilities and transition matrix.
Week - 10 Poisson process.
Week - 11 Gaussian Process
Week - 12 Birth and Death Processes.
Week - 13 Queuing Theory and Models.

Learning Activities and Teaching Methods

  • Teaching Methods
  • Lecture
  • Discussion
  • Question & Answer
  • Drill - Practise
  • Problem Solving
  • Competences
  • Rational
  • Questoning
  • Problem solving
  • Information Management
  • Elementary computing skills
  • Decision making

Assessment Methods

Assessment Method and Passing Requirements
Quamtity Percentage (%)
Toplam (%) 0
  • Info on the Institution
  • Name and Adress
  • Academic Calendar
  • Academic Authorities
  • General Description
  • List of Programmes Offered
  • General Admission Requirements
  • Recognition of Prior Learning
  • Registration Procedures
  • ECTS Credit Allocation
  • Academic Guidance
  • Info on Degree Programmes
  • Doctorate Degree / Proficieny in Arts
  • Master's Degree
  • Bachelor's Degree
  • Associate Degree
  • Open&Distance Education
  • Info for Students
  • Cost of living
  • Accommodation
  • Meals
  • Medical Facilities
  • Facilities for Special Needs Students ı
  • Insurance
  • Financial Support for Students
  • Student Affairs Office
  • Info for Students
  • Learning Facilities
  • International Programmes r
  • Practical Information for Mobile Students
  • Language courses
  • Internships
  • Sports and Leisure Facilities
  • Student Associations