COURSE UNIT TITLE

: LINEAR STATISTICAL MODELS

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
STA 5031 LINEAR STATISTICAL MODELS 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 AYLIN ALIN

Offered to

Statistics
Statistics
STATISTICS

Course Objective

To teach the basic theory of linear statistical models through the concepts and tools of matrix and linear algebra and distribution theory.

Learning Outcomes of the Course Unit

1   Understanding basic concepts of linear and matrix algebra
2   Understanding the concept of Generalized Inverses
3   Solving linear systems
4   Understanding the general linear model
5   Obtaining the distribution of sample mean and covariance matrix
6   Making statistical inference for the general linear model

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Notation for Vector and Matrix Algebra, Basic definitions and properties
2 Properties of special matrices
3 Properties of special matrices
4 Generalized inverses
5 Solutions to linear systems
6 The general Linear Model definition and examples, Preparing Individual Assignments
7 The least squares approach, estimable functions
8 Gauss Markov Theorem, Generalized least squares
9 Multivariate normal distribution and its properties, Preparing Individual Assignments
10 Distributions of quadratic forms
11 Distribution of the sample mean and covariance matrix
12 Properties of least squares estimators, general linear hypotheses, Preparing Individual Assignments
13 Confidence Intervals and multiple comparisons
14 Restricted and Reduced Model

Recomended or Required Reading

Textbook:
Ravishanker, N., Dey, D.K.A First Course in Linear Model Theory , 2001, Chapman and Hall/CRC

Planned Learning Activities and Teaching Methods

Lecture, Homeworks.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 ASG 1 ASSIGNMENT 1
2 ASG 2 ASSIGNMENT 2
3 ASG 3 ASSIGNMENT 3
4 FIN FINAL EXAM
5 FCG FINAL COURSE GRADE ASG 1 + ASG 2 + ASG 3/3 * 0.40 + FIN * 0.60
6 RST RESIT
7 FCGR FINAL COURSE GRADE (RESIT) ASG 1 + ASG 2 + ASG 3/3 * 0.40 + RST * 0.60


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Evaluation of homework assignments 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: aylin.alin @deu.edu.tr
Tel: 0232 301 85 72

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Preparation for final exam 1 55 55
Preparing assignments 3 20 60
Preparations before/after weekly lectures 14 3 42
Final 1 2 2
TOTAL WORKLOAD (hours) 201

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.15555
LO.25555
LO.35555
LO.45555
LO.55555
LO.65555

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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