COURSE UNIT TITLE

: MULTIVARIATE STATISTICS

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
STA 5058 MULTIVARIATE STATISTICS 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 ESIN FIRUZAN

Offered to

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

Course Objective

The objective of this course is to cover a high level of Multivariate Statistics and its applications.

Learning Outcomes of the Course Unit

1   Understanding statistical concepts of linear algebra terms (rank, determinant, eigenvalu, eigenvector etc.),
2   Obtaining multivariate descriptive statistics (mean vector, variance-covariance matrix, correlation matrix etc.),
3   Interpreting three or more dimensional graphs,
4   Applying Principal Component Analysis,
5   Applying Factor Analysis,
6   Applying Discriminant Analysis for two multivariate normal populations.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Types of variables, Data Matrices and Vectors, Data Subscripts
2 The Multivariate Normal Probability Density Function, Bivariate Normal Distributions
3 Mean Vectors and Variance-Covariance, Correlation and Standardized data matrices
4 Three-Dimensional Data Plots, Plots of Higher Dimensional Data, Preparing Individual Assignments
5 Multivariate Normal Distribution Contour Plot
6 Eigenvalues and eigenvectors, Geometric Descriptions
7 Eigenvalues and eigenvectors, Geometric Descriptions
8 Principal Components Analysis on the Variance-Covariance Matrix , Preparing Individual Assignments
9 Estimation of Principal Components, PCA on the Correlation Matrix P
10 Objectives of Factor Analysis, Factor Analysis Equations, Preparing Individual Assignments
11 Choosing the Appropriate Number of Factors, Rotating Factors
12 Classification and Discriminant for two Multivariate Normal Populations, Preparing Individual Assignments
13 Cost Functions and Prior Probabilities,
14 A General Discriminant Rule (Two Populations)

Recomended or Required Reading

Textbook(s): Johnson, R.A. ve Wichern, D.W., (2007), Applied Multivariate Statistical Analysis, 6th Edn, Pearson International Edition.
Supplementary Book(s): Johnson, D.E. (1998) Applied Multivariate Methods for Data Analysts, Duxbury.

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)

DEU Fen Fakültesi Istatistik Bölümü
e-posta: s.alpaykut@deu.edu.tr
Tel: 0232 301 85 56

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 36 36
Preparing assignments 4 25 100
Final 1 2 2
TOTAL WORKLOAD (hours) 208

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

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