COURSE UNIT TITLE

: INTRODUCTION TO BAYESIAN STATISTICS

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
IST 3114 INTRODUCTION TO BAYESIAN STATISTICS ELECTIVE 3 0 0 5

Offered By

Statistics

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

PROFESSOR DOCTOR ÖZLEM EGE ORUÇ

Offered to

Statistics
Statistics(Evening)

Course Objective

This course provides a basic grounding in the theory and concepts of Bayesian inference.

Learning Outcomes of the Course Unit

1   To understand the basic notions of Bayesian statistics
2   To prove and use Bayes Theorem in its various forms
3   To carry out Bayesian Inference for binomial proportion
4   To carry out Bayesian Inference for mean of normal distribution
5   To be able to carry out a test of hypothesis using a full Bayesian methodology
6   To understand the differences between classical statistics and Bayesian statistics

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 The Bayesian paradigm
2 Logic, Probability and Uncertainty
3 Bayesian Inference for Binomial Proportion (Using a Uniform Prior and Beta Prior)
4 Bayesian Inference for Binomial Proportion (Using a choosing your Prior)
5 Comparing Bayesian and Frequentist Inferences for Proportion
6 Bayesian Inference for Normal Mean with a discrete Prior
7 Bayesian Inference for Normal Mean with a continuous prior
8 Some examples of Bayesian Inference for Normal Mean with a discrete and continous Prior
9 Bayesian Inference for Normal Mean with a choosing your Normal prior
10 Bayesian Inference for difference between Means(Equal Variances)
11 Bayesian Inference for difference between Means(Unequal Variances)
12 Bayesian Inference for difference between two proportions using Normal approximation.
13 Bayesian Inference for Simple Linear Regression
14 Robust Bayesian Methods

Recomended or Required Reading

Textbook(s): W.M.Bolstad, Introduction to Bayesian Statistics , JohnWiley&Sons,2004, ISBN 0-471-27020-2(cloth)
Supplementary Book(s): J. Albert ,Bayesian Computation with R 2nd edition, Springer,2009, ISBN 978-0-387-92297-3

Planned Learning Activities and Teaching Methods

The course consists of lecture, class discussion and homework.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 ASG ASSIGNMENT
3 FINS FINAL EXAM
4 FCG FINAL COURSE GRADE MTE * 0.30 + ASG * 0.20 + FIN * 0.50
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + ASG * 0.20 + RST * 0.50


Further Notes About Assessment Methods

None

Assessment Criteria

%30(midtermexam)+%20(Homework Assignments/Presentation/Oral Exam)+%50(final exam)

Language of Instruction

English

Course Policies and Rules

Reading the related parts of the course material each week, attending the course and participating in class discussions are the requirements of the course. 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 www.fef.deu.edu.tr

Contact Details for the Lecturer(s)

DEU. Faculty Sciences Department of Statistics
e-mail: ozlem.ege@deu.edu.tr
Tel: 0232 3018558

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 12 2 24
Preparation for midterm exam 1 10 10
Preparation for final exam 1 20 20
Preparing assignments 2 8 16
Final 1 2 2
Midterm 1 2 2
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.15434
LO.25434
LO.35434
LO.45434
LO.55434
LO.65434

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

HOME / ABOUT US / DEGREE PROGRAMMES / GENERAL INFORMATION FOR STUDENTS / INTERNATIONAL RELATIONS