COURSE UNIT TITLE

: STOCHASTIC PROCESSES

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
IST 4113 STOCHASTIC PROCESSES ELECTIVE 3 0 0 5

Offered By

Statistics

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

PROFESSOR DOCTOR UMAY ZEYNEP UZUNOĞLU KOÇER

Offered to

Statistics
Statistics(Evening)

Course Objective

The objective of this course is to give an introduction to stochastic processes. To express the stochastic system, it gives basic definitions and introduces the students some basic applied stochastic processes. It is expected that the students learn the system can be predictable and controllable if the structure and the variability of the system can be expressed with probability rules.

Learning Outcomes of the Course Unit

1   Expressing basic definitions of stochastic processes
2   Classifying the stochastic processes according to different basic properties
3   Associating the Markov Chains with the real life problems
4   Defining a system using the properties of the Exponential and the Poisson distribution
5   Explaining Markov Chains and Poisson processes with examples
6   Analysing the system using birth and death processes
7   Suggesting solutions and giving offers in order to optimize the system using the Markov decision processes
8   Giving offers for a system, which can be modeled by Markov Chains or birth and death processes, to work better

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to stochastic processes and basic concepts
2 Stochastic Processes with Discrete Parameter Spaces: Definitions and applied examples
3 n-step transition probabilities, Chapman-Kolmogorov equations, first-passage and first-return probabilities.
4 Classification of states of Markov Chains
5 Steady state probabilities and limiting behavior
6 Markov decision processes
7 Examples of Markov decision processes
8 Recitation
9 Midterm
10 Definition of continuous parameter Markov Chains and counting process
11 Poisson process
12 Properties of exponential distribution and the convolutions of exponential variables
13 Distribution of the time between arrivals and the waiting times and generalization of the Poisson process
14 Introduction to birth and death processes
15 Birth and death processes

Recomended or Required Reading

Textbook(s):
Ross S., Introduction to Probability Models, Academic Press, 2003.
Supplementary Book(s):
Erhan Çınlar, Introduction to Stochastic Processes, Prentice Hall, 1975.
Sheldon Ross, Stochastic Processes, Wiley Series in Probability and Mathematical Statistics, 1996.

Planned Learning Activities and Teaching Methods

Lecture and problem solving.

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 * 0.30 + FIN * 0.40
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + ASG * 0.30 + RST * 0.40


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Evaluation of midterm exam and homework

Language of Instruction

Turkish

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 undergraduate policy at http://web.deu.edu.tr/fen

Contact Details for the Lecturer(s)

DEU Fen Fakültesi Istatistik Bölümü
e-mail: umay.uzunoglu@deu.edu.tr
Tel: 0232 301 85 60

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Preparations before/after weekly lectures 14 1 14
Preparation for midterm exam 1 24 24
Preparation for final exam 1 24 24
Preparing assignments 1 0 0
Final 1 4 4
Midterm 1 5 5
TOTAL WORKLOAD (hours) 113

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13PO.14
LO.1544
LO.2544
LO.355454
LO.4535454
LO.5535454
LO.6535454
LO.75354454
LO.8554454

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

Copyright 2015 DEÜ. BİD

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