Objectives and competences
Students:
- will learn basic statistical methods in geography,
- get acquainted with usage of those methods in scientific, research and pedagogical work,
- using basic statistical methods, students will perceive basic statistical concepts and methods of statistical work: quantitative processing and analysis of statistical geospatial data, determining principles in mass occurrences, quantitative conveyance of principles and qualitative valuation,
- also acquire basic ability in computer data processing.
- developing digital literacy.
Content (Syllabus outline)
1. Basic concepts in statistics (population, sample, unit, variable).
2. Geographical sampling methods.
3. Geographical databases – collecting data, managing and developing spatial databases.
4. Univariate statistical methods in geography
5. Bivariate statistical methods in geography
6. Multivariate statistical methods in geography
Learning and teaching methods
- lecture,
- case method
- computer exercises
Intended learning outcomes - knowledge and understanding
Students:
- acquire ability to process, analyse and quantitatively valuate empirical data of mass occurrences through use of statistical methods,
- may, on a basis of critical analysis of empirical data and based on quantitative expressing of principles, critically valuate geographic occurrences and processes in geographic space and substantiate principles through research work,
- may efficiently use basic statistical methods for research and pedagogical work.
Intended learning outcomes - transferable/key skills and other attributes
- a student will gain ability to understand actual mass occurrences in geographic space through use of statistical methods,
- based on statistical methods, students can solve real professional problems and develop skills and routines in usage of knowledge, especially in the field of geography.
Readings
Ivajnšič, D. 2020: Kvantitativne metode v geografiji : zbirka vaj z rešitvami. Maribor: Filozofska fakulteta, Fakulteta za naravoslovje in matematiko, 2020. 1 spletni vir, ilustr. https://ff.um.si/o-fakulteti/oddelki/oddelek-za-geografijo/
Ivajnšič, D., Geografski informacijski sistemi : zbirka vaj. Maribor: Fakulteta za naravoslovje in matematiko, 2019. 1 spletni vir (1 datoteka PDF ([138] str.)), ilustr. https://biologija.fnm.um.si/studij/studijska-gradiva/ Košmelj K. 2007. Uporabna statistika. Druga dopolnjena izdaja. Ljubljana, Biotehniška fakulteta.
Pfajfar L., Arh F. 2004: Statistika 1, Ekonomska fakulteta, UL, Ljubljana. (https://repozitorij.uni-lj.si/IzpisGradiva.php?id=17699&lang=slv&prip=dkum:984539:d5).
Vsako študijsko leto bo seznam študijske literature posodobljen./ The list of study literature will be updated each school year.
Prerequisits
Conditions for inclusion in work: none.
Additional information on implementation and assessment - computer skills, 50 %
- written exam. 50 %
