CANKIRI KARATEKIN UNIVERSITY Bologna Information System


  • Course Information
  • Course Title Code Semester Laboratory+Practice (Hour) Pool Type ECTS
    Geostatistics TYB560 FALL-SPRING 3+0 Faculty E 6
    Learning Outcomes
    1-Calculates descriptive statistics.
    2-Analyzes the relationships between more than one variable.
    3-Analyzes correlation function, semivariogram and crossover semivariogram.
    4-Creates spatial interpolation by using kriging, cokriging and inverse distance methods.
    5-Evaluates the results obtained regarding the variables and data quality (post evaluation).
  • ECTS / WORKLOAD
  • ActivityPercentage

    (100)

    NumberTime (Hours)Total Workload (hours)
    Course Duration (Weeks x Course Hours)14342
    Classroom study (Pre-study, practice)14342
    Assignments207749
    Short-Term Exams (exam + preparation) 0000
    Midterm exams (exam + preparation)3011515
    Project0000
    Laboratory 0000
    Final exam (exam + preparation) 5013030
    0000
    Total Workload (hours)   178
    Total Workload (hours) / 30 (s)     5,93 ---- (6)
    ECTS Credit   6
  • Course Content
  • Week Topics Study Metarials
    1 Descriptive statistics R1
    2 Multiple relationship analysis R1
    3 Graphical Analysis of Spatial Data Sets R1
    4 Correlation Function and Covariance Function R1
    5 Semivariogram and its modeling R1
    6 Isotropic analysis R1
    7 Directional analysis R1
    8 Local and global forecasting R1
    9 Spatial estimation methods R1
    10 Reverse distance method R1
    11 Ordinary kriging R1
    12 Ordinary block kriging R1
    13 Ordinary cokriging R1
    14 Prediction Criteria R1
    Prerequisites -
    Language of Instruction Turkish
    Responsible Assoc. Prof. Dr. Gülay KARAHAN
    Instructors

    1-)Doçent Dr. Gülay Karahan

    Assistants -
    Resources R1: Edward H. Isaacs, R. Moham Srivastava. 1989. Applied Geostatistics. Oxford University, Press.
    Supplementary Book -
    Goals The aim of the course is to give wisdom on descriptive data analysis, univariate and bivariate analysis, modeling of spatial structure, modeling of anisotropic structure, and use of geostatistical methods in spatial estimation.
    Content -
  • Program Learning Outcomes
  • Program Learning Outcomes Level of Contribution
    1 To build a new skills and knowledge on undergraduate -
    2 To use the data in interdisciplinary and professional works. 4
    3 To transfer knowledge in interdisciplinary studies -
    4 To win the knowledge and skills that will make someone successful in academic career 4
    5 To get skills to work in interdisciplinary teams. -
    6 To get skills for solving and evaluating a problem 4
    7 Must be able to evaluate quality process and develop managing plans. -
    8 To have knowledge about entrepreneurship and innovation issues. 3
    9 To reach the actual scientific knowledge by using communication and computer technologies. 5
    10 To transfer the knowledge about agriculture and life sciences by using modern techniques and equipment -
    11 To have advanced oral and written communication skills -
    12 To communicate and follow literature about agriculture and nature sciences by using a foreign language. -
    13 To behave professionally and obey ethic values about vocational issues. -
    14 To gain awareness and ability on environment and natural resources protection and to inform the public on these issues -
    Çankırı Karatekin Üniversitesi  Bilgi İşlem Daire Başkanlığı  @   2017 - Webmaster