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
  • Institute of Graduate Programmes
  • Department of Statistics
  • Master of Science (MS) Degree
  • Program in Statistical Theory
  • Course Structure Diagram with Credits
  • Theory of Statistics
  • Description
  • Description
  • Learning Outcomes
  • Course's Contribution to Prog.
  • Learning Outcomes & Program Qualifications
  • ECTS Credit Load

Course Introduction Information

Code - Course Title İST530 - Theory of Statistics
Course Type Required Courses
Language of Instruction Türkçe
Laboratory + Practice 3+0
ECTS 7.5
Course Instructor(s) PROFESÖR DOKTOR YELİZ MERT KANTAR
Mode of Delivery Face-to-face theoretical lecturesBoard and/or presentation-based instructionDeductive problem-solving sessionsWeekly assignments and theoretical exercisesOccasional computer-assisted demonstrations (Monte Carlo simulations)
Prerequisites
Courses Recomended
Required or Recommended Resources
Recommended Reading List
Assessment methods and criteria
Work Placement
Sustainability Development Goals

Content

Weeks Topics
Week - 1 EN: Introduction to Statistical Theory
Week - 2 EN:Random Variables, Probability Distributions
Week - 3 EN: Introduction to Estimation Theory
Week - 4 EN: Maximum Likelihood Estimation (MLE)
Week - 5 EN: Estimation using the Moment Method, OLS method
Week - 6 EN: Sufficiency and Fisher Information
Week - 7 EN: Cramér–Rao Lower Bound
Week - 8 Applications
Week - 9 EN: Statistical Decision Making
Week - 10 EN: Monte Carlo Methods and Numerical Simulation
Week - 11 EN: Introduction to hypothesis testing, test and power functions.
Week - 12 EN: EN: Test Finding Methods: Likelihood Ratio Tests
Week - 13 EN: Reading and evaluating articles
Week - 14 EN: Reading and evaluating articles

Learning Activities and Teaching Methods

  • Competences
  • Productive
  • Questoning
  • Entrepreneur
  • Eleştirel düşünebilme
  • Abstract analysis and synthesis
  • Problem solving
  • Applying theoretical knowledge into practice
  • Concern for quality
  • Elementary computing skills

Assessment Methods

Assessment Method and Passing Requirements
Quamtity Percentage (%)
2.Midterm Exam 1 40
Final Exam 1 60
Toplam (%) 100
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