Eskisehir Technical University Info Package Eskisehir Technical University Info Package
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About the Program Educational Objectives Key Learning Outcomes Course Structure Diagram with Credits Field Qualifications Matrix of Course& Program Qualifications Matrix of Program Outcomes&Field Qualifications
  • Graduate School of Sciences
  • Department of Statistics
  • Master of Science (MS) Degree
  • Course Structure Diagram with Credits
  • Applied Multivariate Statistical Analysis
  • Description
  • Description
  • Learning Outcomes
  • Course's Contribution to Prog.
  • Learning Outcomes & Program Qualifications

Course Introduction Information

Code - Course Title İST551 - Applied Multivariate Statistical Analysis
Course Type Elective Courses
Language of Instruction Türkçe
Laboratory + Practice 3+0
ECTS 7.5
Course Instructor(s) DOÇENT ÖZER ÖZDEMİR
Mode of Delivery The mode of delivery of this course is face to face.
Prerequisites There is no prerequisites or requisites for this course.
Courses Recomended There is no recommended optimal programme component for this course.
Recommended Reading List Applied Multivariate Statistical Analysis, Johson and Wichern, Pearson Ed., USA
Assessment methods and criteria 1 midterm, homework, final exam.
Work Placement N/A
Sustainability Development Goals

Content

Weeks Topics
Week - 1 Basic Concepts
Week - 2 Situations for Simple Linear Regression and Multivariate Regression
Week - 3 Analysis of Multivariate Regression Models
Week - 4 Computer Applications of Multivariate Regression Models
Week - 5 Factor Analysis
Week - 6 Principal Component Analysis: Dimensionality Reduction
Week - 7 Logistic Regression
Week - 8 Binary Models(logit, probit,tobit)
Week - 9 Canonical Correlation Analysis
Week - 10 Discriminant Analysis
Week - 11 Clustering Analysis
Week - 12 Clustering Analysis: Hierarchical Methods
Week - 13 Clustering Analysis: Nonhierarchical Methods
Week - 14 General Evaluation of Multivariate Statistical Methods and Applications with Package Programs

Learning Activities and Teaching Methods

  • Teaching Methods
  • Lecture
  • Discussion
  • Question & Answer
  • Team/Group Work
  • Drill - Practise
  • Problem Solving
  • Brain Storming
  • Report Preparation and/or Presentation
  • Proje Design/Management
  • Competences
  • Productive
  • Rational
  • Questoning
  • Entrepreneur
  • Creative
  • Follow ethical and moral rules
  • Effective use of Turkish
  • Effective use of a foreign language
  • Work in teams
  • Use time effectively
  • Problem solving
  • Applying theoretical knowledge into practice
  • Information Management
  • To work autonomously
  • Organization and planning
  • Elementary computing skills
  • To work in interdisciplinary projects
  • Project Design and Management
  • Leadership
  • To work in international projects

Assessment Methods

Assessment Method and Passing Requirements
Quamtity Percentage (%)
2.Midterm Exam 1 30
Homework 1 20
Final Exam 1 50
Toplam (%) 100
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