Course Unit Code  Course Unit Title  Type of Course Unit  Year of Study  Semester  Number of ECTS Credits  İST404  APPLICATIONS OF MULTIVARIATE STATISTICS  Compulsory  4  8  7 

Level of Course Unit 
First Cycle 
Objectives of the Course 
To make the students learn the Multivariate Statistical Analysis Methods and apply them in computer environment 
Name of Lecturer(s) 
Assoc. Prof. Dr. Hakan Savaş SAZAK 
Learning Outcomes 
1  To know which Multivariate Statistical Analysis is appropriate for a problem in a research project  2  To know how to conduct the required operations on data and prepare the required tables and graphics using MS Excel software  3  To be able to determine whether Univariate or Multivariate data are normally distributed  4  To be able to detect possible outliers in Multivariate data  5  To be able to conduct the application of ANOVA and MANOVA in computer environment  6  To be able to conduct the application of Multivariate Regression in computer environment  7  To be able to conduct Principal Components and Factor Analysis in computer environment  8  To be able to conduct Classification and Discriminant Analysis in computer environment  9  To be able to conduct Cluster Analysis in computer environment  10  To be able to conduct Multidimensional Scaling in computer environment 

Mode of Delivery 
Face to Face 
Prerequisites and corequisities 
None 
Recommended Optional Programme Components 
It is advised that students took the course Multivariate Statistics 
Course Contents 
To know which Multivariate Statistical Analysis is appropriate for a problem in a research project ; To know how to conduct the required operations on data and prepare the required tables and graphics using MS Excel software; To be able to determine whether Univariate or Multivariate data are normally distributed; To be able to detect possible outliers in Multivariate data; To be able to conduct the application of ANOVA and MANOVA in computer environment; To be able to conduct the application of Multivariate Regression in computer environment; To be able to conduct Principal Components and Factor Analysis in computer environment; To be able to conduct Classification and Discriminant Analysis in computer environment; To be able to conduct Cluster Analysis in computer environment; To be able to conduct Multidimensional Scaling in computer environment 
Weekly Detailed Course Contents 

1  Introduction of Multivariate Statistical Analysis Methods    2  Introduction of MS Excel    3  Preparation of Tables, creation of various statistical functions and graphs using MS Excel    4  Construction of QQ graph and detection of possible outliers using MS Excel    5  Obtaining the mean vector, the variancecovariance matrix and the Mahalanobis distance of data using MS Excel    6  Check of Multivariate normality and BoxCox transformation using MS Excel    7  Conducting tests based on means and constructing confidence intervals using MS Excel    8  Midterm Exam    9  MANOVA    10  Multivariate Regression    11  Principal Components Analysis    12  Factor Analysis    13  Classification and Discriminant Analysis    14  Cluster Analysis    15  Multidimensional Scaling    16  Final Exam   

Recommended or Required Reading 
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  
Midterm Examination  1  100  SUM  100  
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 

Workload Calculation 