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
  • Linear Models
  • Description
  • Description
  • Learning Outcomes
  • Course's Contribution to Prog.
  • Learning Outcomes & Program Qualifications

Course Introduction Information

Code - Course Title İST531 - Linear Models
Course Type Required Courses
Language of Instruction Türkçe
Laboratory + Practice 3+0
ECTS 7.5
Course Instructor(s)
Mode of Delivery The mode of delivery of this course is Face to face
Prerequisites There is no prerequisite or co-requisite for this course.
Courses Recomended It is suggested for students to take İST 307 Regression analysis course.
Recommended Reading List
Assessment methods and criteria 1 Mid-term, 1 Final exam
Work Placement N/A
Sustainability Development Goals

Content

Weeks Topics
Week - 1 Some fundamental mathematical concepts
Week - 2 Matrix, determinant and quadratic forms
Week - 3 derivation of matrix and vector
Week - 4 Idemptent matrix
Week - 5 Multivariate normal distribution
Week - 6 Noncentral Chi-square distribution
Week - 7 Noncentral F distribution
Week - 8 Distribution of quadratic forms
Week - 9 Expectation of quadratic forms and indepentence of quadratic forms
Week - 10 Linear models
Week - 11 Application of linear models
Week - 12 Application of linear models
Week - 13 Interval estimator for linear models
Week - 14 hypothesis tests for linear models

Learning Activities and Teaching Methods

  • Teaching Methods
  • Lecture
  • Discussion
  • Question & Answer
  • Drill - Practise
  • Case Study
  • Problem Solving
  • Brain Storming
  • Report Preparation and/or Presentation

Assessment Methods

Assessment Method and Passing Requirements
Quamtity Percentage (%)
Toplam (%) 0
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