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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS EKO 6060 STATISTICAL DECISION THEORY ELECTIVE 3 0 0 6

Offered By

Econometrics

Level of Course Unit

Third Cycle Programmes (Doctorate Degree)

Course Coordinator

ASSOCIATE PROFESSOR ISTEM KÖYMEN

Offered to

Econometrics

Course Objective

The main objective of the course is give base ideas and results with reference to mechanism of Statistical decision-making.

Learning Outcomes of the Course Unit

1   To be able to make a practice of Theory of Bayesian. 2   To be able to solve decision processes using decision trees. 3   To be able to make a practice of statistical procedures based on risk in optimal decision-making processes. 4   To be able to compare the basic elements of the decision theory 5   To be able to form systems of prior probabilities known.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Statistical Modelling: Basic concepts and elements 2 Statistical Modelling: Inference 3 Statistical Decision Theory's base elements 4 Expected Loss, Decision Rules and Risk 5 Decision Principles, Decision Trees 6 Utility and harm: Utility Theory 7 Utility and harm: Money Program, Loss function 8 Mid Term 9 Prior information and subjective probability 10 Bayesian analysis 11 Bayesian analysis 12 Minimax Analysis 13 Implementations 14 Implementations

Recomended or Required Reading

Statistical Decision Theory and Bayesian Analysis,by James O. Berger, Springer., 1980

Planned Learning Activities and Teaching Methods

This course will be presented using methods of expression, discussion and solving problem.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MTE MIDTERM EXAM 2 STT TERM WORK (SEMESTER) 3 FIN FINAL EXAM 4 FCG FINAL COURSE GRADE MTE * 0.30 + STT * 0.30 + FIN* 0.40 5 RST RESIT 6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + STT * 0.30 + RST* 0.40

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)

Yrd. Doç.Dr.Istem Keser Istem.koymen@deu.edu.tr

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 13 3 39 Preparations before/after weekly lectures 13 3 39 Preparation for midterm exam 1 35 35 Preparation for final exam 1 35 35 Midterm 1 3 3 Final 1 3 3 TOTAL WORKLOAD (hours) 154

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 1 1 1 1 1 1 1 1 1 LO.3 2 2 2 2 2 2 2 2 2 LO.4 2 2 2 2 2 2 2 2 2 LO.5 2 2 2 2 2 1 1 1 1