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
  • Remote Sensing and Geographical Information Syst.
  • Master of Science (MS) Degree
  • Course Structure Diagram with Credits
  • Spatial Statistics
  • Description
  • Description
  • Learning Outcomes
  • Course's Contribution to Prog.
  • Learning Outcomes & Program Qualifications
  • ECTS Credit Load

Course Introduction Information

Code - Course Title UCS559 - Spatial Statistics
Course Type Required Courses
Language of Instruction Türkçe
Laboratory + Practice 3+0
ECTS 7.5
Course Instructor(s) DOÇENT DOKTOR EMRAH PEKKAN
Mode of Delivery This course is given only face to face. 
Prerequisites There is no prerequisite or co-requisite for this course.
Courses Recomended Basic level knowledge of statistics is needed in this course.
Required or Recommended Resources
Recommended Reading List
Assessment methods and criteria 2 midterm exams, 1 final exam 
Work Placement Not Applicable
Sustainability Development Goals Industry, Innovation and Infrastructure , Sustainable Cities and Communities , Climate Action

Content

Weeks Topics
Week - 1 Introduction to Statistics
Week - 2 Introduction to Spatial Statistics
Week - 3 Centrographic Statistics
Week - 4 Exercise 1
Week - 5 Ponit Pattern Analysis
Week - 6 Exercise 2
Week - 7 Spatial Autocorrelation
Week - 8 Spatial Autokorelation in Regional Scale
Week - 9 Exercise 3
Week - 10 Spatial Autocorrelation in Local Scale
Week - 11 Exercise 4
Week - 12 Correlation
Week - 13 Clasical Regression Model and Spatial Alternatives
Week - 14 Exercise 5

Learning Activities and Teaching Methods

  • Teaching Methods
  • Lecture
  • Discussion
  • Question & Answer
  • Team/Group Work
  • Drill - Practise
  • Case Study
  • Competences
  • Questoning
  • Abstract analysis and synthesis
  • Problem solving
  • To work autonomously
  • Decision making
  • Project Design and Management

Assessment Methods

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