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Lecturer(s)
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Macků Karel, Mgr. Ph.D.
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Dobešová Zdena, doc. Ing. Ph.D.
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Course content
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The course extends the existing statistical methods by incorporating the spatial component of data. It also introduces further advanced analyses and data processing methods. Practical exercises are carried out primarily using the R language. 1. Advanced exploratory data anylsis, data conversion and manipulation 2. Spatial statistics 3. Geographically weighted methods 4. Spatial regression models 5. Logistic regression 6. Application of fuzzy sets theory in GI 6. Application of information theory in GI 7. Shape and spatial metrics for data analysis in GIS 8. Application of fractal geometry in GI 9. Kernel density estimation
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Learning activities and teaching methods
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Lecture, Monologic Lecture(Interpretation, Training), Laboratory Work
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Learning outcomes
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The aim of the course is to familiarise students with advanced and less common methods of data processing and analysis, which place particular emphasis on the spatial aspect of the data.
To acquire knowledge of advanced spatial analysis, spatial statistics and geocomputation. Upon completion of the course, students will be able to define key concepts, describe and appropriately select the main methods of data processing, and demonstrate both theoretical knowledge and practical skills in solving model problems.
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Prerequisites
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Basic knowledge of KGI/DATAM Data Mining course and KGI/STAME course.
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Assessment methods and criteria
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Written exam
Theoretical and practical knowledge of presented topics.
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Recommended literature
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Andres, J., Fišer, J., Rypka, M. (2015). Dynamické systémy 3 : úvod do teorie deterministického chaosu a fraktální geometrie. Olomouc.
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Baddeley, A., et al. (2015). Spatial Point Patterns. New York.
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Brunsdon, Ch., Comber, L. An Introduction to R for Spatial Analysis and Mapping. 2025.
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Fotheringham, S. et al. Geographically Weighted Regression. 1996.
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Haining, R. Spatial Data Analysis: Theory and Practice. Cambridge. 2003.
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Pászto V. (2015). Prostorová informace a vybrané metody geocomputation pro její hodnocení, doktorská práce. Olomouc.
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