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FACULTY of SCIENCE / DEPARTMENT of STATISTICS and COMPUTER SCIENCES /
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IST4020Multivariate Statistical Analysis4+0+0ECTS:6
Year / SemesterSpring Semester
Level of CourseFirst Cycle
Status Compulsory
DepartmentDEPARTMENT of STATISTICS and COMPUTER SCIENCES
Prerequisites and co-requisitesNone
Mode of DeliveryFace to face
Contact Hours14 weeks - 4 hours of lectures per week
LecturerDr. Öğr. Üyesi Uğur ŞEVİK
Co-LecturerAss. Prof. Dr. Türkan E. Dalkılıç
Language of instructionTurkish
Professional practise ( internship ) None
 
The aim of the course:
The aim of this course is to teach analysis methods about multivariate variables.
 
Learning OutcomesCTPOTOA
Upon successful completion of the course, the students will be able to :
LO - 1 : make inferences about multi- dimensional parameters1,2,61
LO - 2 : develop the ability of thinking in multi-dimensions1,2,61
LO - 3 : get the ability of calculating on multi -dimensional distribution and variables1,2,61
LO - 4 : do analysis about multi-dimensional data by using computer1,2,61
CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), LO : Learning Outcome

 
Contents of the Course
Normal distribution with multi variable, T2 statistics of Hotelling, multi-variance analysis, generalized MANOVA, scales with repetition and profile analysis, classification and definition, correlation, factory analysis.
 
Course Syllabus
 WeekSubjectRelated Notes / Files
 Week 1Basic definitions and concepts: Matrices, determinants, eigenvalues and eigenvectors
 Week 2Two-dimensional random variables, the marginal probability and distribution functions, expected value of two-dimensional random variables
 Week 3Independence, characteristic function, covariance and correlation, conditional distributions
 Week 4Normal distribution, Normal distribution of two variables, marginal, conditional distributions
 Week 5Some characteristics of the normal distribution probability, moments
 Week 6The concept of multi-dimensional normal distribution
 Week 7Maximum likelihood estimators of the normal distribution of multiple users, review and problem solving
 Week 8Mid-term exam
 Week 9Correlation matrix, the conditional normal distribution
 Week 10Correlation coefficient: simple, partial, multi
 Week 11Hypothesis testing in correlation coefficients, distribution of Wishost
 Week 12t distribution and F distribution, expected value and variance
 Week 13Multiple analysis of variance MANOVA
 Week 14Important Components Analysis (ICA)
 Week 15Differential Factor Analysis (DFA), general review, problem solving and examples
 Week 16End-of-term exam
 
Textbook / Material
1Tatlidil, H. (1996). Uygulamalı Çok Değişkenli İstatistiksel Analiz, Akademi Matbaası, Ankara.
 
Recommended Reading
1Alpar, R. (1997). Uygulamalı Çok Değişkenli İstatistiksel Yöntemlere Giriş I, Bağırhan Yayınevi, Ankara.
2Tuncer, Y. (2002). Çok değişkenli İstatistik Analize Giriş: Normal Teori, Bıçaklar Kitapevi, Ankara.
3Johnson, R. A. and Wichern, D. W. (1982). Applied Multivariate Statistical Analysis, Prentice-Hall.
 
Method of Assessment
Type of assessmentWeek NoDate

Duration (hours)Weight (%)
Mid-term exam 9 08/04/2015 1,5 50
End-of-term exam 16 28/05/2015 1,5 50
 
Student Work Load and its Distribution
Type of workDuration (hours pw)

No of weeks / Number of activity

Hours in total per term
Yüz yüze eğitim 6 14 84
Sınıf dışı çalışma 5 14 70
Laboratuar çalışması 0 0 0
Arasınav için hazırlık 15 1 15
Arasınav 0 1 0
Uygulama 0 0 0
Klinik Uygulama 0 0 0
Ödev 8 2 16
Proje 0 0 0
Kısa sınav 0 0 0
Dönem sonu sınavı için hazırlık 18 1 18
Dönem sonu sınavı 1 2 2
Diğer 1 0 0 0
Diğer 2 0 0 0
Total work load205