COURSE UNIT TITLE

: DECISION THEORY

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
STA 5102 DECISION THEORY ELECTIVE 3 0 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

Offered to

Statistics (English)
STATISTICS (ENGLISH)
Statistics (English)

Course Objective

The objective of the course is to describe the basic ingredients of decision theory, for individuals and for groups, and to apply the theory to a variety of interesting and important problems.

Learning Outcomes of the Course Unit

1   Defining basic concepts of decision problems
2   Using mathematical techniques to model decision problems
3   Finding the optimum decisions both under risk and uncertainty
4   Analyzing sequential decision problems
5   Interpreting the solutions of decision problems
6   Gaining both theoretical and practical skills applying decision models to different areas

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to the ideas of decision analysis
2 Decision making under uncertainty
3 Decision making under risk
4 Applications, preparing individual assignments
5 Utility theory
6 Utility theory
7 MIDTERM
8 Decision trees - how to draw and how to solve
9 Decision trees - how to draw and how to solve
10 Bayes theorem and decision making with sample information, preparing individual assignments
11 Bayes decision making with binomial distribution
12 Bayes decision making with binomial distribution, preparing presentations
13 Bayes decision making with normal distribution, preparing presentations
14 Bayes decision making with normal distribution

Recomended or Required Reading

Textbook(s):
J.Q. Smith, Decision Analysis - A Bayesian Approach, Chapman & Hall, 1988, (paperback).
D.V. Lindley, Making Decisions, (2nd edition), Wiley (1985), paperback.
S. French, Decision Theory: An Introduction to the Mathematics of Rationality, Ellis Horwood,
Chichester (1986), (paperback).
M.H. DeGroot, Optimal Statistical Decisions, McGraw-Hill.
R.T. Clemen, Making Hard Decisions, (2nd edition), Duxbury Press (1995).
Supplementary Book(s):

Planned Learning Activities and Teaching Methods

Lecture, homework and problem solving.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 ASG ASSIGNMENT
3 PRS PRESENTATION
4 FIN FINAL EXAM
5 FCG FINAL COURSE GRADE MTE* 0.30 + ASG * 0.20 + PRS * 0.10 + FIN * 0.40
6 RST RESIT
7 FCGR FINAL COURSE GRADE (RESIT) MTE* 0.30 + ASG * 0.20 + PRS * 0.10 + 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 exams, homework and presentations.

Language of Instruction

English

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.

Contact Details for the Lecturer(s)

DEU Fen Fakültesi Istatistik Bölümü
e-mail: cengiz.celikoglu@deu.edu.tr
Tel: 0232 301 85 50

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Preparing assignments 2 20 40
Preparing presentations 2 10 20
Preparation for midterm exam 1 15 15
Preparation for final exam 1 20 20
Preparations before/after weekly lectures 14 4 56
Final 1 2 2
Midterm 1 2 2
TOTAL WORKLOAD (hours) 197

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.15
LO.2555
LO.354
LO.454
LO.55544
LO.6545454