548-0092/01 – Interpretation of geodata (IGD)

 Gurantor department Department of Geoinformatics Credits 3 Subject guarantor doc. Ing. Igor Ivan, Ph.D. Subject version guarantor doc. Ing. Igor Ivan, Ph.D. Study level undergraduate or graduate Requirement Compulsory Year 2 Semester summer Study language Czech Year of introduction 2015/2016 Year of cancellation Intended for the faculties HGF Intended for study types Bachelor
Instruction secured by
CAH0021 Mgr. Jan Caha, Ph.D.
IVA026 doc. Ing. Igor Ivan, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent

Subject aims expressed by acquired skills and competences

- Student demonstrates knowledge: • basics of working with the program R • selected statistical methods - Students can: • edit the data matrix • apply selected statistical methods • reduce the size of the input data matrix - Student is able to: • interpret the results • extract the maximum information from the supplied data and geodata

Tutorials

Summary

This course is focused on a practical work with data, its pre-processing, formatting and transformations. Practical introduction of basic statistical methods of data dimensions reduction and other multivariate methods such as factor, discriminant and cluster analysis and decision trees. Also basic principles of data mining are introduced. The aspect of results interpretation and maximal mining of information from data and geodata are key aspects of this course.

Compulsory literature:

ZUUR, A. F., IENO, E. N., MEESTERS, E. (2009): A Beginner's Guide to R. Springer, 236 p. DALGAARD, P. (2008): Introductory Statistics with R. Springer, 380 p. EVERITT, B., HOTHORN, T. (2011): An Introduction to Applied Multivariate Analysis with R. Springer, 288 p.

Recommended literature:

SPECTOR, P. (2008): Data Manipulation with R. Springer, 164 p. FLOWERDEW, R., MARTIN, D. (eds.) (2005): Methods in Human Geography: A Guide for Students Doing a Research Project. Prentice Hall, 392 p.

E-learning

No other requirements are defined.

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

1) Methods of pre-processing of data and geodata for further processing 2) Errors in data and geodata and dealing with errors 3) Basics in R 4) R and geodata 5) Principal component analysis and interpretation of results 6) Factor analysis and interpretation of results 7) Discriminant analysis and interpretation of results 8) Cluster analysis and interpretation of results 9) Decision trees and interpretation of results 10)Basics of data mining

Conditions for subject completion

Combined form (validity from: 2015/2016 Winter semester)
Min. number of points
Mandatory attendence parzicipation:

Show history

Occurrence in study plans

Academic yearProgrammeField of studySpec.FormStudy language Tut. centreYearWSType of duty
2019/2020 (B1316) Geodesy, Cartography and Geoinformatics (3646R006) Geoinformatics P Czech Ostrava 2 Compulsory study plan
2019/2020 (B1316) Geodesy, Cartography and Geoinformatics (3646R006) Geoinformatics K Czech Ostrava 2 Compulsory study plan
2018/2019 (B1316) Geodesy, Cartography and Geoinformatics (3646R006) Geoinformatics K Czech Ostrava 2 Compulsory study plan
2018/2019 (B1316) Geodesy, Cartography and Geoinformatics (3646R006) Geoinformatics P Czech Ostrava 2 Compulsory study plan
2017/2018 (B1316) Geodesy, Cartography and Geoinformatics (3646R006) Geoinformatics P Czech Ostrava 2 Compulsory study plan
2017/2018 (B1316) Geodesy, Cartography and Geoinformatics (3646R006) Geoinformatics K Czech Ostrava 2 Compulsory study plan
2016/2017 (B1316) Geodesy, Cartography and Geoinformatics (3646R006) Geoinformatics K Czech Ostrava 2 Compulsory study plan
2016/2017 (B1316) Geodesy, Cartography and Geoinformatics (3646R006) Geoinformatics P Czech Ostrava 2 Compulsory study plan
2015/2016 (B1316) Geodesy, Cartography and Geoinformatics (3646R006) Geoinformatics P Czech Ostrava 2 Compulsory study plan
2015/2016 (B1316) Geodesy, Cartography and Geoinformatics (3646R006) Geoinformatics K Czech Ostrava 2 Compulsory study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner