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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS EKO 6066 STOCHASTICAL PROCESS ELECTIVE 3 0 0 6

Offered By

Econometrics

Level of Course Unit

Third Cycle Programmes (Doctorate Degree)

Course Coordinator

ASSOCIATE PROFESSOR MURAT TANIK

Offered to

Econometrics

Course Objective

To teach the concepts of Conditional Probability and Conditional Expected Value, to introduce the understanding of Marko Chains, to show the applications of Markov Decision Processes in social sciences.

Learning Outcomes of the Course Unit

1   To be able to apply Conditional Probability and Conditional Expectation Value. 2   To be able to make business economics applications related to Compound Random Variables 3   To be able to use Markov models to solve problems in business, economics and marketing. 4   To be able to make applications related to Markov Decision Processes

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Conditional Probability and Conditional Expectation Theory 1 2 Discrete Random Variables and Applications on Continuous Random Variables 2 3 Compound Random Variables and Applications 3 4 Compound Random Variables and Applications 4 5 Introduction to Markov Chains and Related Fundamental Theorems 5 6 Example Problems with Markov Chains 6 7 Random Walk Model 7 8 Midterm 8 9 Midterm 9 10 Random Walk Model Related Applications 10 11 Chapman-Kolmogorov Equations 11 12 Applications of Chapman-Kolmogorov Equations 12 13 Markov Decision Processes 13 14 Hidden Markov Chains 14

Recomended or Required Reading

Introduction to Probability Models, Elsevier Inc. Sheldon Rose

Planned Learning Activities and Teaching Methods

Lecture Method, Proof Method, Discussion Method and Problem Solving Method

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MTE MIDTERM EXAM 2 FCG FINAL COURSE GRADE 3 FCGR FINAL COURSE GRADE MTE * 0.40 + FCG* 0.60 4 RST RESIT 5 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.40 + RST* 0.60

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

To be announced.

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) TOTAL WORKLOAD (hours) 0

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 PO.7 PO.8 PO.9 LO.1 2 2 2 2 2 2 2 2 2 LO.2 2 2 2 2 2 2 2 2 2 LO.3 2 2 2 2 2 2 2 2 2 LO.4 2 2 2 2 2 2 2 2 2