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
  • Theory of Statistics
  • Description
  • Description
  • Learning Outcomes
  • Course's Contribution to Prog.
  • Learning Outcomes & Program Qualifications

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)
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 There is no prerequisite or co-requisite for this course.
Recommended Reading List
Assessment methods and criteria 2 Mid-terms, 1 Final exam
Work Placement N/A
Sustainability Development Goals

Content

Weeks Topics
Week - 1 Introduction to probability theory.
Week - 2 Probability distribution: Discrete and continuous distributions; multivariate distributions.
Week - 3 Some inequalities: Markov, chebyshev, Hölder, Minkovski, and Jensen.
Week - 4 Principle of data reduction: the sufficient principle, likelihood principle.
Week - 5 Point Estimation:
Week - 6 Methods of finding estimator; Method of moment, maximum likelihood asymptotic properties of maximum likelihood,
Week - 7 Applications of finding methods of estimators
Week - 8 Fisher information matrix, bayes estimators, invariant estimator.
Week - 9 Methods of evaluating estimators: Mean square error, best unbiased estimators.
Week - 10 Hypothesis testing: methods of finding test, likelihood ratio test, Walt test,
Week - 11 Hypothesis testing: Lagrange multipliers test, invariant test, bayesian test, asymptotic distribution of LRTs.
Week - 12 Applications of hypothesis testing
Week - 13 Methods of evaluating test: Power function, unbiased and invariant test.
Week - 14 Interval estimation: Methods of finding interval estimator.

Learning Activities and Teaching Methods

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  • Question & Answer
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  • Brain Storming
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  • Productive
  • True to core values
  • Follow ethical and moral rules

Assessment Methods

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