COURSE UNIT TITLE

: MULTIVARIATE ANALYSIS

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
STA 6011 MULTIVARIATE ANALYSIS 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 this course is to cover theoretical structure of multivariate analysis

Learning Outcomes of the Course Unit

1   Understanding the importance of inference with multivariate normal distribution,
2   To understand the multivariate distributions,
3   To develop the multivariate large sample distributions and approximations,
4   To understand the multivariate central limit theorems,
5   To determine the Wishart and related distributions,
6   To compare the several multivariate means.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Expectation and Covariance Operators
2 Mahalanobis Distances and Angles
3 Multivariate Normal Distribution, Moments of Multivariate Distributions, marginal normal distributions
4 Convergence of a sequence of matrices, convergence of a series of matrices, Preparing Individual Assignments
5 Asymptotic Distribution of a Function of a random matrix
6 Wishart Distribution, Inverted Wishart Distribution, the noncentral wishart distribution
7 Hotelling T-square Distribution, student t-type distribution, beta-type distribution
8 Comparing two normal populations, transforming to normality, distributional tests and plots, Preparing Individual Assignments
9 Multivariate linear models
10 Least squares estimation, properties of least squares estimates, Preparing Individual Assignments
11 Maximum Likelihood Estimation
12 Multivariate analysis of variance, Preparing Individual Assignments
13 One-way MANOVA, One-way MANCOVA
14 Two-way MANOVA, Two-way MANCOVA

Recomended or Required Reading

Textbook(s): Timm, N.H. Applied Multivariate Analysis, (2002), Springer.
Supplementary Book(s): Seber, G.A.F. (1984), Multivariate Observations, Wiley
Press S.J., (1972), Applied Multivariate Analysis, HRW Press

Planned Learning Activities and Teaching Methods

Lecture, homework assignments, problem solving, presentation

Assessment Methods

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


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

Further Notes About Assessment Methods

If the instructor needs to add some explanation or further note, this column can be selected from the DEBIS menu

Assessment Criteria

Evaluation of homework assignments, presentation, project report 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)

To be announced.

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Preparations before/after weekly lectures 14 2 28
Preparation for final exam 1 40 40
Preparing assignments 4 25 100
Final 1 2 2
TOTAL WORKLOAD (hours) 212

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
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Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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