          Description of Individual Course Units
 Course Unit Code Course Unit Title Type of Course Unit Year of Study Semester Number of ECTS Credits İST401 MULTIVARIATE STATISTICS Compulsory 4 7 8
Level of Course Unit
First Cycle
Objectives of the Course
To make the students learn the Multivariate Statistics concepts and required terminology and to give them the theoretical fundamentals which will be needed for higher level analysis in the area.
Name of Lecturer(s)
Assoc. Prof. Dr. Hakan Savaş SAZAK
Learning Outcomes
 1 To know the Multivariate Statistics Data Structure and how to express them in matrix format 2 To know the calculation of Multivariate Descriptive Statistics 3 To know the concepts and properties of the mean vector, the variance-covariance matrix, the correlation matrix etc. based on population and sample 4 To know the Multivariate Graphical Display methods 5 To know the calculation of eigenvalues and eigenvectors and their properties and usage in the area 6 To know the statistical distance concept and its usage in the area 7 To know the properties of Multivariate Normal distribution 8 To know the Multivariate Moment and Cumulant Generating Functions and their properties 9 To know the transitions and relationships between the Multivariate distributions 10 To be able to conduct the Multivariate tests and construct the related confidence intervals
Mode of Delivery
Face to Face
Prerequisites and co-requisities
None
Recommended Optional Programme Components
None
Course Contents
The Multivariate Statistics Data Structure and their expression matrix format; The Multivariate Descriptive Statistics and their calculation; The concepts and properties of the mean vector, the variance-covariance matrix, the correlation matrix etc. based on population and sample; Graphical Displays; Eigenvalues and eigenvectors; The statistical distance concept; The Multivariate Normal distribution and its properties; The Multivariate Moment and Cumulant Generating Functions and their properties; Check of Multivariate Normality and data transformation ; The transitions and relationships between the Multivariate distributions; Marginal and Conditional distributions; Hotelling T2 and simultaneous confidence intervals; The tests based on the comparison of various samples and the related confidence intervals ; The tests related to matched comparisons for Multivariate Normal distribution and the related confidence intervals ; The hypothesis tests based on the Repeated Measures Design and the related confidence intervals ; MANOVA
Weekly Detailed Course Contents
 Week Theoretical Practice Laboratory 0 The Multivariate Statistics Data Structure and their expression matrix format, the Multivariate Descriptive Statistics and their calculation 1 The concepts and properties of the mean vector, the variance-covariance matrix, the correlation matrix etc. based on population and sample 2 Graphical displays, eigenvalues and eigenvectors and their properties 3 The statistical distance concept 4 The Multivariate Normal distribution and its properties 5 The Multivariate Moment and Cumulant Generating Functions and their properties 6 Check of Multivariate Normality and data transformation 7 Midterm Exam 8 The transitions and relationships between the Multivariate distributions 9 Marginal and Conditional distributions 10 Hotelling T2 and simultaneous confidence intervals 11 The tests based on the comparison of various samples and the related confidence intervals 12 The tests related to matched comparisons for Multivariate Normal distribution and the related confidence intervals 13 The hypothesis tests based on the Repeated Measures Design and the related confidence intervals 14 MANOVA 15 Final Exam
Applied Multivariate Statistical Analysis (R. A. Johnson & D. W. Wichern, Fifth Edition, 2002) Özdamar, K., Paket Programlar ile İstatistiksel Veri Analizi Tatlıdil, H., Uygulamalı Çok Değişkenli İstatistiksel Analiz
Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"
Assessment Methods and Criteria
 Term (or Year) Learning Activities Quantity Weight Midterm Examination 1 100 SUM 100 End Of Term (or Year) Learning Activities Quantity Weight Final Sınavı 1 100 SUM 100 Term (or Year) Learning Activities 40 End Of Term (or Year) Learning Activities 60 SUM 100
Language of Instruction
English
Work Placement(s)
None 