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Lecturer(s)
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Podlena Jaroslav, Mgr. Ph.D.
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Course content
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Basics of software control R via RStudio Graphs in the ggplot2 library Quantitative data, variables and their types Visualization of qualitative vs. quantitative variables Bar charts, pie chartsHistograms, box graphs Scatter plotsWord clouds Data visualization on a map base Time lines Visualizations for professional publications vs. average
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Learning activities and teaching methods
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Lecture with practical applications, Practicum
- Graduate study programme term essay (40-50)
- 50 hours per semester
- Presentation preparation (report in a foreign language) (10-15)
- 15 hours per semester
- Practical training (number of hours)
- 26 hours per semester
- Contact hours
- 13 hours per semester
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| prerequisite |
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| Knowledge |
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| to characterize and explain basic descriptive statistics (eg average, median, range) |
| to recognize professional work based on the methodology of quantitative surveys |
| Skills |
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| to master basic functions in MS Excel environment (or equivalent software) |
| critically reflect and understand a professional text in the English language |
| Competences |
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| N/A |
| N/A |
| N/A |
| learning outcomes |
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| Knowledge |
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| to design a suitable graphical presentation of data |
| to explain the difference between graphic presentation for professional purposes and for the media |
| Skills |
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| to master the basic functions of the R software in the Studio environment |
| to master more advanced graphing functions in the ggplot2 library in the R software |
| to interpret graphical outputs in published data correctly |
| to propose a procedure for the presentation of one's own data and to accompany it with a verbal or written comment |
| Competences |
|---|
| N/A |
| N/A |
| N/A |
| teaching methods |
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| Knowledge |
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| Interactive lecture |
| Group discussion |
| Self-study of literature |
| Textual studies |
| Skills |
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| Practicum |
| Group discussion |
| Self-study of literature |
| Textual studies |
| Skills demonstration |
| Competences |
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| Interactive lecture |
| Practicum |
| Skills demonstration |
| Textual studies |
| Self-study of literature |
| Group discussion |
| assessment methods |
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| Knowledge |
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| Continuous assessment |
| Skills demonstration during practicum |
| Group presentation at a seminar |
| Seminar work |
| Skills |
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| Continuous assessment |
| Skills demonstration during practicum |
| Group presentation at a seminar |
| Individual presentation at a seminar |
| Seminar work |
| Competences |
|---|
| Skills demonstration during practicum |
| Seminar work |
| Individual presentation at a seminar |
| Group presentation at a seminar |
| Continuous assessment |
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Recommended literature
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Agresti, Alan; Finlay, Barbara. Statistical methods for the social sciences. Upper Saddle River : Pearson Prentice Hall, 2009. ISBN 978-0-13-027295-7.
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Hebák, Petr. Vícerozměrné statistické metody [1]. Praha : Informatorium, 2004. ISBN 80-7333-025-3.
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Hendl, Jan. Přehled statistických metod zpracování dat : analýza a metaanalýza dat. Praha : Portál, 2004. ISBN 80-7178-820-1.
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Kabacoff R. R in action: data analysis and graphics with R.. Shelter Island, NY: Manning Publications Co., 2011.
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Krzanowski, W. J. Principles of multivariate analysis : a user's perspective. Rev. ed. Oxford : Oxford University Press, 2000. ISBN 0-19-850708-9.
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Legendre, Pierre; Legendre, Louis. Numerical ecology. 2nd english ed. Amsterdam : Elsevier, 1998. ISBN 0-444-89249-4.
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Shennan, Stephen. Quantifying archaeology. 2nd ed. Iowa City : University of Iowa Press, 1997. ISBN 0-87745-598-8.
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Wickham, H. ggplot2: elegant graphics for data analysis. Springer, 2016.
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