ISB423 Multivariate Statistical Analysis

5 ECTS - 3-0 Duration (T+A)- 7. Semester- 3 National Credit

Information

Code ISB423
Name Multivariate Statistical Analysis
Term 2024-2025 Academic Year
Semester 7. Semester
Duration (T+A) 3-0 (T-A) (17 Week)
ECTS 5 ECTS
National Credit 3 National Credit
Teaching Language Türkçe
Level Lisans Dersi
Type Normal
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator Prof. Dr. GÜLESEN ÜSTÜNDAĞ ŞİRAY
Course Instructor Prof. Dr. GÜLESEN ÜSTÜNDAĞ ŞİRAY (A Group) (Ins. in Charge)


Course Goal / Objective

The goal is to construct the necessary theoretical background for multivariate statistical analysis.

Course Content

The content of this course is basic concepts of multivariate statistics, multivariate normal distribution, testing hypothesis about the multivariate data.

Course Precondition

NaN

Resources

1. Alvin C. Rencher. Methods of Multivariate Analysis (2nd Edition) Wiley series in probability and mathematical statistics 2. Using Multivariate Statistics (6th Edition). Barbara G. Tabachnick , Linda S. Fidell. Pearson Education, Boston. 3. Uygulamalı Çok değişkenli İstatistiksel Analiz. Hüseyin Tatlıdil

Notes

UC Irvine Machine Learning Repository-https://archive.ics.uci.edu/


Course Learning Outcomes

Order Course Learning Outcomes
LO01 Define the basic concepts of multivariate statistics.
LO02 Explain the purpose of using of multivariate statistics.
LO03 Determine the mean vector, variance-covariance and correlation matrices for multivariate data.
LO04 Explain the probability density function, marginal probability density function, conditional distribution and statistical independency for multivariate distributions with examples .
LO05 Find the moment generating function for multivariate normal distribution.
LO06 Find marginal probability density function, conditional probability density function for multivariate normal distribution.
LO07 Make the parameter estimates for multivariate normal distribution.
LO08 Test the hypothesis about the multivariate data.


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 Bilgi - Kuramsal, Olgusal Explain the essence fundamentals and concepts in the field of Statistics
PLO02 Bilgi - Kuramsal, Olgusal Emphasize the importance of Statistics in life 4
PLO03 Bilgi - Kuramsal, Olgusal Define basic principles and concepts in the field of Law and Economics
PLO04 Bilgi - Kuramsal, Olgusal Produce numeric and statistical solutions in order to overcome the problems
PLO05 Bilgi - Kuramsal, Olgusal Use proper methods and techniques to gather and/or to arrange the data 4
PLO06 Bilgi - Kuramsal, Olgusal Utilize computer programs and builds models, solves problems, does analyses and comments about problems concerning randomization
PLO07 Bilgi - Kuramsal, Olgusal Apply the statistical analyze methods 4
PLO08 Bilgi - Kuramsal, Olgusal Make statistical inference (estimation, hypothesis tests etc.)
PLO09 Bilgi - Kuramsal, Olgusal Generate solutions for the problems in other disciplines by using statistical techniques and gain insight
PLO10 Bilgi - Kuramsal, Olgusal Discover the visual, database and web programming techniques and posses the ability of writing programs
PLO11 Beceriler - Bilişsel, Uygulamalı Distinguish the difference between the statistical methods
PLO12 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Make oral and visual presentation for the results of statistical methods
PLO13 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Have capability on effective and productive work in a group and individually
PLO14 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği 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
PLO15 Yetkinlikler - Öğrenme Yetkinliği Develop scientific and ethical values in the fields of statistics-and scientific data collection


Week Plan

Week Topic Preparation Methods
1 Basic concepts of multivariate statistics Source reading Öğretim Yöntemleri:
Anlatım, Soru-Cevap
2 Matrix theory for multivariate statistical analysis Source reading Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Problem Çözme
3 Matrix theory for multivariate statistical analysis 2 Source reading Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Problem Çözme
4 Mean vector, variance-covariance matrix, correlation matrix Source reading Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Problem Çözme, Alıştırma ve Uygulama
5 Probability density function, marginal probability density function, conditional distribution and statistical independency for multivariate distributions Source reading Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Problem Çözme, Alıştırma ve Uygulama
6 Probability density function, characteristic functions, moments, moment generating function and parameter estimates Source reading Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Problem Çözme
7 Maximum likelihood estimators for population parameters Source reading Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Problem Çözme
8 Mid-Term Exam Review the topics discussed in the lecture notes and sources. Ölçme Yöntemleri:
Yazılı Sınav
9 Marginal normal distribution, conditional normal distribution Source reading Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Problem Çözme, Alıştırma ve Uygulama
10 Distribution of linear relations, independency of subvector variables Source reading Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Problem Çözme, Alıştırma ve Uygulama
11 Obtaining the parameters given the density function Source reading Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Problem Çözme
12 Multivariate test methods (likelihood ratio test) Source reading Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Problem Çözme
13 Multivariate test methods (composition-intersection test) Source reading Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Problem Çözme
14 Test on mean vectors Source reading Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Problem Çözme, Alıştırma ve Uygulama
15 Test on covariance matrices, Testing hypothesis with statistical package programs. Source reading Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Problem Çözme, Alıştırma ve Uygulama
16 Term Exams Review the topics discussed in the lecture notes and sources. Ölçme Yöntemleri:
Yazılı Sınav
17 Term Exams Review the topics discussed in the lecture notes and sources. Ölçme Yöntemleri:
Yazılı Sınav


Student Workload - ECTS

Works Number Time (Hour) Workload (Hour)
Course Related Works
Class Time (Exam weeks are excluded) 14 3 42
Out of Class Study (Preliminary Work, Practice) 14 3 42
Assesment Related Works
Homeworks, Projects, Others 0 0 0
Mid-term Exams (Written, Oral, etc.) 1 12 12
Final Exam 1 18 18
Total Workload (Hour) 114
Total Workload / 25 (h) 4,56
ECTS 5 ECTS

Update Time: 12.06.2024 10:45