Eskisehir Technical University Info Package Eskisehir Technical University Info Package
  • Info on the Institution
  • Info on Degree Programmes
  • Info for Students
  • Türkçe
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
  • Spatial Statistics
  • Description
  • Description
  • Learning Outcomes
  • Course's Contribution to Prog.
  • Learning Outcomes & Program Qualifications

Course Introduction Information

Code - Course Title İST3501 - Spatial Statistics
Course Type Area Elective Courses
Language of Instruction İngilizce
Laboratory + Practice 2+1
ECTS 5.0
Course Instructor(s) ARAŞTIRMA GÖREVLİSİ DOKTOR CENK İÇÖZ
Mode of Delivery Face to face
Prerequisites None
Courses Recomended
Required or Recommended Resources Moraga, Paula. (2023). Spatial Statistics for Data Science: Theory and Practice with R. Chapman & Hall/CRC Data Science Series. ISBN 9781032633510https://www.paulamoraga.com/book-spatial/index.htmlAn Introduction to R for Spatial Analysis and Mapping
Recommended Reading List
Assessment methods and criteria midterm and project or final exam
Work Placement
Sustainability Development Goals

Content

Weeks Topics
Week - 1 Spatial Data and Types: Definitions and application areas
Week - 2 Descriptive Statistics on Spatial Data
Week - 3 Spatial Exploratory Data Analysis
Week - 4 Spatial Point Patterns and types
Week - 5 Spatial Point Patterns (quadrat analysis, complete spatial randomness, clustered and regular patterns and their visualization)
Week - 6 Spatial Point Pattern Applications
Week - 7 Areal (Lattice) Patterns: Autocorrelation analysis in Spatial Patterns (global and local statistics)
Week - 8 Areal (Lattice) Pattern Applications
Week - 9 Spatial regression models
Week - 10 Applications of spatial regression models
Week - 11 Geostatistical Data : Kriging, Inverse Distance Weighting
Week - 12 Applications Related to Geostatistical Data
Week - 13 Project presentations
Week - 14 Project presentations

Learning Activities and Teaching Methods

  • Teaching Methods
  • Lecture
  • Discussion
  • Question & Answer
  • Drill - Practise
  • Case Study
  • Problem Solving
  • Brain Storming
  • Report Preparation and/or Presentation
  • Proje Design/Management
  • Competences
  • Productive
  • Rational
  • Questoning
  • Effective use of a foreign language
  • Eleştirel düşünebilme
  • Abstract analysis and synthesis
  • Information Management
  • Decision making
  • To work in interdisciplinary projects

Assessment Methods

Assessment Method and Passing Requirements
Quamtity Percentage (%)
1.Midterm Exam 1 40
Final Exam 1 60
Toplam (%) 100
  • Info on the Institution
  • Name and Adress
  • Academic Calendar
  • Academic Authorities
  • General Description
  • List of Programmes Offered
  • General Admission Requirements
  • Recognition of Prior Learning
  • Registration Procedures
  • ECTS Credit Allocation
  • Academic Guidance
  • Info on Degree Programmes
  • Doctorate Degree / Proficieny in Arts
  • Master's Degree
  • Bachelor's Degree
  • Associate Degree
  • Open&Distance Education
  • Info for Students
  • Cost of living
  • Accommodation
  • Meals
  • Medical Facilities
  • Facilities for Special Needs Students ı
  • Insurance
  • Financial Support for Students
  • Student Affairs Office
  • Info for Students
  • Learning Facilities
  • International Programmes r
  • Practical Information for Mobile Students
  • Language courses
  • Internships
  • Sports and Leisure Facilities
  • Student Associations