COURSE UNIT TITLE

: ADVANCED STATISTICAL INFERENCE - I

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
STA 6001 ADVANCED STATISTICAL INFERENCE - I 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

PROFESSOR DOCTOR BURCU HÜDAVERDI

Offered to

Statistics
Statistics
STATISTICS

Course Objective

To equip the participants with the theoretical statistical tools a Ph.D. statistician must have.

Learning Outcomes of the Course Unit

1   Understanding fields of sets and probability measure
2   Understanding the advanced theory of random variables and their distributions
3   Determining the distribution functions of measurable functions of random variables
4   Generating moments and cumulants of distributions
5   Investigating expected value of a random variable and its properties
6   Obtaining characteristic functions of distributions

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Set Theory, Sample spaces and events
2 Fields of Set
3 Probability Measure, Extension of Probability Measure
4 Conditional Probability and Statistical Independence, Random Variables
5 Distribution Functions, Density and Mass Functions, Problems
6 Multiple Random Variables, Joint and Marginal Distributions, Conditional Distributions and Independence
7 Bivariate, Multivariate Distributions, Dependence and Copula
8 Special Distribution functions of one, two, k-dimensional random variables, Problems
9 Midterm
10 Functions of Random Variables,
11 Expected Value, conditional expected value and Properties
12 Moments and Moment Generating Functions, properties and applications
13 Charactersitic Functions, properties and applications
14 Determination of distribution functions from moments

Recomended or Required Reading

Textbook:
Casella G. & Berger R. L., Statistical Inference, Second Edition, Brooks/Cole, 2002.
Wilks S.S, Mathematical Statistics, John Wiley & Sons,1962.
Lehmann E. L. Testing Statistical Hypothesis, Wiley, 1986.

Planned Learning Activities and Teaching Methods

Lecture and Homeworks

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 ASG ASSIGNMENT
2 MTE MIDTERM EXAM
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE ASG * 0.30 + MTE * 0.30 + FIN * 0.40
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) ASG * 0.30 + MTE * 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 homework assignments, midterm and final exam.

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. 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: burcu.hudaverdi @deu.edu.tr
Tel: 0232 301 85 97

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 14 3 42
Preparation for final exam 1 36 36
Preparing assignments 2 20 40
Preparation for midterm exam 1 27 27
Final 1 2 2
Midterm 1 2 2
TOTAL WORKLOAD (hours) 188

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.1555
LO.2555
LO.3555
LO.4555
LO.5555
LO.6555

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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