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Lecturer(s)
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Fiedor David, doc. Mgr. Ph.D.
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Course content
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1. Introduction to computer work in data analysis, basics of controlling special software for data processing 2. Repetition of basic statistical concepts, frequency processing of a statistical file 3. Descriptive statistics - calculation of basic statistical characteristics of the whole set and its sub-sets 4. Theoretical frequency distributions and method of estimating parameters of normal frequency distribution 5. Transformation of variables, selection of cases 6. Introduction to testing statistical hypotheses, methods of verifying data normality 7. Parametric and non-parametric tests of hypotheses about distribution parameters 8. Analysis of variance and its non-parametric analogy 9. Basics of correlation analysis - contingency table and chi square test 10. Analysis of dependences of two cardinal features 11. Basics of regression analysis - focused on a linear regression model.
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Learning activities and teaching methods
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Lecture, Monologic Lecture(Interpretation, Training), Dialogic Lecture (Discussion, Dialog, Brainstorming), Work with Text (with Book, Textbook), Demonstration
- Attendace
- 26 hours per semester
- Homework for Teaching
- 34 hours per semester
- Preparation for the Course Credit
- 30 hours per semester
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Learning outcomes
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The course will follow the introductory acquaintance with statistical methods in the subject Statistical Methods in Geography 1, at the same time it will use the knowledge of students acquired in subjects using data sources from various areas of geography. Students will get acquainted not only with the MS Excel program, but also with the STATISTICA program.
Select and apply a suitable method for statistical analysis of geographic data and then correctly interpret the results.
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Prerequisites
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KGG/STM1
KGG/DSTM1
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Assessment methods and criteria
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Mark, Oral exam, Written exam, Student performance, Dialog, Seminar Work
Requirements: attendance (two absences are tolerated) and obtaining a sufficient number of points from two continuous papers. Requirements for the exam: knowledge in the range of lectures and study literature, the ability to independently analyze the collected data to work using statistical software.
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Recommended literature
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Frankfort-Nachmias, Ch., Leon-Guerrero, A. (2017). Social Statistics for a Diverse Society. Los Angeles: Sage Publications.
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Rogerson, P.A. (2015). Statistical methods for Geography: A student's guide. Sage Publications.
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Řezanková, H. (2010). Analýza dat z dotazníkových šetření. Professional Publishing.
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