Course: Methods of Regional Geographical Research II

« Back
Course title Methods of Regional Geographical Research II
Course code KEM/MRGV2
Organizational form of instruction Lecture + Seminar
Level of course Master
Year of study not specified
Semester Summer
Number of ECTS credits 5
Language of instruction Czech
Status of course unspecified
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
Lecturer(s)
  • Gangur Mikuláš, Doc. RNDr. Ph.D.
Course content
1. Continuous, discontinuous variable in geographic practice 2. Causality of variables ,applications in regional geography 3. Theoretical distribution of variables; theory and practice 4. Basics of regression analysis, its modelling, real vs. theoretical values 5. Nonlinear regression models 6. Transformation of variables (for different types of regression models) 7. Multivariate linear regression 8. Multidimensional more complex techniques - introduction 9. Cluster analysis 10. Principle component analysis 11. Factor analysis 12. Canonical correspondence analysis - introduction, basic principles 13. Graphical presentation of the results of multivariate analysis

Learning activities and teaching methods
E-learning, Collaborative instruction, Individual study, Students' self-study, Textual studies, Lecture, Lecture with visual aids, Seminar
  • Contact hours - 39 hours per semester
  • Preparation for an examination (30-60) - 45 hours per semester
  • Graduate study programme term essay (40-50) - 40 hours per semester
  • Presentation preparation (report) (1-10) - 10 hours per semester
prerequisite
professional knowledge
Preconditions for successful graduation of the course contain basic knowledge of simple statistical techniques, abilities like an orientation in statistical data and their sources. The main ability is to correctly identify the studied problem and to choose useful data and a correct method necessary for effective solution. These abilities and skills including elementary graphical visualisation of statistical data will be required.
learning outcomes
Students are able: - to understand principles of processing and evaluating of multivariate statistical data, - to know in detail with techniques such as multivariate regression, cluster and factor analysis, - can analyze and evaluate data using statistical software.
teaching methods
Lecture
Lecture with visual aids
Seminar
E-learning
Textual studies
Collaborative instruction
Students' self-study
Individual study
assessment methods
Oral exam
Skills demonstration during seminar
Seminar work
Recommended literature
  • GODDARD, J., B. An introduction to factor analysis. 1976.
  • Halás, M., Klapka, P., Kladivo P. Distance-decay functions for daily travel-to-work flows. 2014.
  • Kladivo, P., Ptáček, P., Roubínek, P., Ziener, K. Czech-Polish and Austrian-Slovenian borderland ? similarities and differences of development and typology of regions. 2012.
  • MCGREW, Ch., J., MONROE, Ch. An Introduction to Statistical Problem Solving in Geography. 1999.
  • ROGERSON, A., P. Statistical Methods For Geography: A Students Guide. 2006.


Study plans that include the course
Faculty Study plan (Version) Branch of study Category Recommended year of study Recommended semester