Z2069 Geographical Data Analysis 2

Faculty of Science
Spring 2021
Extent and Intensity
1/1. 3 credit(s). Type of Completion: z (credit).
Teacher(s)
prof. RNDr. Petr Dobrovolný, CSc. (lecturer)
RNDr. Jan Divíšek, Ph.D. (lecturer)
Mgr. Milan Fila (seminar tutor)
Mgr. Zdeněk Janků (seminar tutor)
Mgr. Lucia Kaplan Pastíriková (seminar tutor)
Guaranteed by
prof. RNDr. Petr Dobrovolný, CSc.
Department of Geography – Earth Sciences Section – Faculty of Science
Contact Person: prof. RNDr. Petr Dobrovolný, CSc.
Supplier department: Department of Geography – Earth Sciences Section – Faculty of Science
Timetable
Mon 1. 3. to Fri 14. 5. Tue 13:00–13:50 Z5,02004
  • Timetable of Seminar Groups:
Z2069/01: Mon 1. 3. to Fri 14. 5. Mon 9:00–9:50 Z1,01001b, M. Fila, Z. Janků, L. Kaplan Pastíriková
Z2069/02: Mon 1. 3. to Fri 14. 5. Mon 10:00–10:50 Z1,01001b, M. Fila, Z. Janků, L. Kaplan Pastíriková
Z2069/03: Mon 1. 3. to Fri 14. 5. Mon 11:00–11:50 Z1,01001b, M. Fila, Z. Janků, L. Kaplan Pastíriková
Course Enrolment Limitations
The course is only offered to the students of the study fields the course is directly associated with.
fields of study / plans the course is directly associated with
there are 12 fields of study the course is directly associated with, display
Course objectives
The main aim of this course is to provide students with an overview of practical use of descriptive statistic. At the end of the course student should be able to understand basic statistical methods explained in individual lectures. He/she would be able to explain when to apply different methods and make reasoned decisions about preconditions that are necessary for proper utilization of methods in question. He/she would be able to work with information on data preparation, make deductions based on acquired knowledge concerning statistical methods and properly interpret results
Learning outcomes
Completing the course students will be able to:
- apply the Analysis of Variance in typical tasks in geography
- choose appropriate methods of the non-parametric statistics in geography
- analyse individual components of times series (trend, periodicity, cycles, noise fraction
- design and practically use methods of multivariate statistics (cluster analysis, principle component analysis)
Syllabus
  • Analysis of variance I – basic terms, the One Factor ANOVA,
  • Analysis of variance II – the Two Factor ANOVA, multiple comparisons
  • Nonparametric statistics – goodness of fit, nonparametric ANOVA
  • Time series analysis I. – model identification, autocorrelation
  • Time series analysis II. – trend analysis, sesonal decomposition
  • Time series analysis III. – introduction to spectral analysis
  • Spatial statistics – principles and simple tools
  • Introduction to multivariate statistics, Principle Component Analysis
  • Cluster analysis - non-hierarchical (k-means) and hierarchical (UPGMA) classification algorithms
Literature
    recommended literature
  • HENDL, Jan. Přehled statistických metod zpracování dat :analýza a metaanalýza dat. Vyd. 1. Praha: Portál, 2004, 583 s. ISBN 8071788201. info
  • BURT, James E., Gerald M. BARBER and David L. RIGBY. Elementary statistics for geographers. 3rd ed. New York: Guilford Press, 2009, xii, 653. ISBN 9781572304840. info
  • ROGERSON, Peter. Statistical methods for geography : a student's guide. 3rd ed. Los Angeles: Sage, 2010, xvi, 348. ISBN 9781848600034. info
  • MAINDONALD, J. H. Data analysis and graphics using R : an example-based approach. Edited by John Braun. New York: Cambridge University Press, 2003, xxiii, 362. ISBN 0521813360. info
  • LEGENDRE, Pierre and Louis LEGENDRE. Numerical ecology. 3rd engl. ed. Amsterdam: Elsevier, 2012, xvi, 990. ISBN 9780444538680. info
Teaching methods
Lectures explaining basic terms and presenting individual examples step by step. Practical training based on 10 exercises that are solved using statistical software.
Assessment methods
Two written tests, the first one practical with the use of computer. Elaboration of all practical excercises is the necessary conditon for passing the exam.
Language of instruction
Czech
Further Comments
Study Materials
The course is taught annually.
The course is also listed under the following terms Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2022, Spring 2023, Spring 2024, Spring 2025.
  • Enrolment Statistics (Spring 2021, recent)
  • Permalink: https://is.muni.cz/course/sci/spring2021/Z2069