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COURSE INFORMATON
Course Title Code Semester L+P Hour Credits ECTS
Multivariate Statistical Analysis * ISB   423 7 3 3 5

 Prerequisites and co-requisites Yok Recommended Optional Programme Components None

Language of Instruction Turkish
Course Level First Cycle Programmes (Bachelor's Degree)
Course Type
Course Coordinator Assoc.Prof.Dr. Gülesen ÜSTÜNDAĞ ŞİRAY
Instructors
 Prof. Dr. SADULLAH SAKALLIOĞLU 1. Öğretim Grup:A Prof. Dr. SADULLAH SAKALLIOĞLU 2. Öğretim Grup:A

Assistants
Goals
To construct the necessary theoretical background for multivariate statistical analysis.
Content
Basic concepts of multivariate statistics, multivariate normal distribution, testing hypothesis about the multivariete data

Learning Outcomes
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Course's Contribution To Program
NoProgram Learning OutcomesContribution
12345
1
Explain the essence fundamentals and concepts in the field of Probability, Statistics and Mathematics
2
Emphasize the importance of Statistics in life
3
Define basic principles and concepts in the field of Law and Economics
4
Produce numeric and statistical solutions in order to overcome the problems
5
Use proper methods and techniques to gather and/or to arrange the data
6
Utilize computer systems and softwares
7
Construct the model, solve and interpret the results by using mathematical and statistical tehniques for the problems that include random events
8
Apply the statistical analyze methods
9
Make statistical inference(estimation, hypothesis tests etc.)
10
Generate solutions for the problems in other disciplines by using statistical techniques
11
Discover the visual, database and web programming techniques and posses the ability of writing programme
12
Construct a model and analyze it by using statistical packages
13
Distinguish the difference between the statistical methods
14
Be aware of the interaction between the disciplines related to statistics
15
Make oral and visual presentation for the results of statistical methods
16
Have capability on effective and productive work in a group and individually
17
Professional development in accordance with their interests and abilities, as well as the scientific, cultural, artistic and social fields, constantly improve themselves by identifying training needs
18
Develop scientific and ethical values in the fields of statistics-and scientific data collection

Course Content
WeekTopicsStudy Materials _ocw_rs_drs_yontem
1 Basic concepts of multivariate statistics Source reading
2 Matrix theory for multivariate statistical analysis Source reading
3 Matrix theory for multivariate statistical analysis Source reading
4 Mean vector, variance-covariance matrix, correlation matrix Source reading
5 Probability density function, marginal probability density function, conditional distribution and statistical independency for multivariate distributions Source reading
6 Probability density function, characteristic functions, moments, moment generating function and parameter estimates Source reading
7 Maximum likelihood estimators for population parameters Source reading
8 Mid-term exam Review the topics discussed in the lecture notes and sources
9 Marginal normal distribution, conditional normal distribution Source reading
10 Distribution of linear relations, independency of subvector variables Source reading
11 Obtaining the parameters given the density function Source reading
12 Multivariate test methods (likelihood ratio test) Source reading
13 Multivariate test methods (composition-intersection test) Source reading
14 Test on mean vectors Source reading
15 Test on covariance matrices, Testing hypothesis with statistical package programs. Source reading
16-17 Final exam Review the topics discussed in the lecture notes and sources