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Lecturer(s)
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Nesrstová Viktorie, Mgr.
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Jašková Paulína, Mgr.
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Římalová Veronika, Mgr.
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Hron Karel, prof. RNDr. Ph.D.
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Talská Renáta, Mgr.
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Štefelová Nikola, Mgr.
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Rendlová Julie, Mgr.
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Course content
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1. Practising knowledge of data import and manipulation 2. How to report and summarize data I 3. How to report and summarize data II 4. How to report and summarize data III 5. How to report and summarize data IV 6. Reporting and summarizing - a real example 7. Graphic presentation of data I 8. Graphic presentation of data II 9. Software R - An introduction 10. Software R - Objects 11. Software R - Factors, arrays, lists, data frames 12. Software R - Some elements of R language 13. Software R - An import from databases
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Learning activities and teaching methods
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Dialogic Lecture (Discussion, Dialog, Brainstorming), Demonstration
- Attendace
- 26 hours per semester
- Homework for Teaching
- 20 hours per semester
- Preparation for the Course Credit
- 40 hours per semester
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Learning outcomes
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Statistical software SAS, SAS EG - data presentation. Introduction to R.
Knowledge - Knowledge of data presentation and basics of R language.
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Prerequisites
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Data import and transformation in statistical software.
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Assessment methods and criteria
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Student performance
Each student has to pass a practical test on PC.
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Recommended literature
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Dalgaard, P. (2008). Introductory Statistics with R. Springer, Heidelberg.
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J. Verzani. (2005). Using R for Introductory Statistics. Washington.
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Matloff, N. (2009). The Art of R Programming. UC Davis.
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Venables, W. N., Smith, D. M., R Core Team. (2014). An Introduction to R. R Foundation for Statistical Computing, Vienna, Austria.
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