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
  • Faculty of Science
  • Department of Statistics
  • Course Structure Diagram with Credits
  • Sampling
  • Description
  • Description
  • Learning Outcomes
  • Course's Contribution to Prog.
  • Learning Outcomes & Program Qualifications

Course Introduction Information

Code - Course Title İST335 - Sampling
Course Type Required Courses
Language of Instruction Türkçe
Laboratory + Practice 4+0
ECTS 6.0
Course Instructor(s) DOÇENT DOKTOR KADİR ÖZGÜR PEKER
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 recommended optional programme component for this course.
Recommended Reading List * Çıngı, H. (1994) Örnekleme Kuramı. Ankara:H.Ü. Fen Fakültesi Basımevi.* Cochran, W.G. (1977) Sampling Techniques.* Ağaoğlu, E. (1998) Uygulamalı Örnekleme. Anadolu Üniversitesi Yayınları No: 10-14.* Yamane, T. (2001) Temel Örnekleme Yöntemleri. Literatür Yayınları:53. (Çeviri)* Özmen, A. (2000) Uygulamalı Araştırmalarda Örnekleme Yöntemleri. Eskişehir: Anadolu Üniversitesi Fen Fakültesi Yayınları, No.17.
Assessment methods and criteria 2 Mid-term and 1 Final Exams. Exams will be applied by classical method.
Work Placement Not available.
Sustainability Development Goals Quality Education , Industry, Innovation and Infrastructure , Partnerships for Purposes

Content

Weeks Topics
Week - 1 Basic concepts and definitions about sampling
Week - 2 Sampling methods
Week - 3 The sample selection process in simple random sampling
Week - 4 Simple estimation in simple random sampling
Week - 5 Estimation of the sample size
Week - 6 Estimation of the sample size
Week - 7 Simple estimation in stratified sampling
Week - 8 Stratified random sampling
Week - 9 Stratified random sampling
Week - 10 Ratio estimations in simple random sampling
Week - 11 Ratio estimations in stratified random sampling
Week - 12 Ratio estimations in stratified random sampling
Week - 13 Systematic sampling
Week - 14 Cluster sampling

Learning Activities and Teaching Methods

  • Teaching Methods
  • Lecture
  • Discussion
  • Question & Answer
  • Demonstration
  • Drill - Practise
  • Case Study
  • Problem Solving
  • Brain Storming
  • Competences
  • Rational
  • Follow ethical and moral rules
  • Use time effectively
  • Abstract analysis and synthesis
  • Problem solving
  • Applying theoretical knowledge into practice
  • Information Management
  • Organization and planning
  • Elementary computing skills
  • Decision making
  • To work in interdisciplinary projects

Assessment Methods

Assessment Method and Passing Requirements
Quamtity Percentage (%)
1.Midterm Exam 1 25
2.Midterm Exam 1 25
Final Exam 1 50
Toplam (%) 100
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