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Lecturer(s)
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Jašková Paulína, Mgr.
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Štefelová Nikola, Mgr.
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Hron Karel, prof. RNDr. Ph.D.
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Nesrstová Viktorie, Mgr.
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Course content
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1. An Introduction 2. Libraries and Data Import 3. Data Import II 4. Data Import and Manipulation I 5. Exercises. 6. Data Import and Manipulation II 7. Data Import and Manipulation III 8. Data Import and Manipulation IV 9. Data Import and Manipulation V 10. Data Import and Manipulation VI 11. SQL I 12. SQL II
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Learning activities and teaching methods
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Dialogic Lecture (Discussion, Dialog, Brainstorming), Demonstration
- Attendace
- 26 hours per semester
- Preparation for the Course Credit
- 40 hours per semester
- Homework for Teaching
- 20 hours per semester
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Learning outcomes
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Working with statistical software SAS and SAS Enterprise Guide - data import and manipulation.
Knowledge - Knowledge of statistical software - data input and manipulations.
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Prerequisites
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Basic PC skills.
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Assessment methods and criteria
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Student performance
Each student has to import and transform an assigned data file and to pass on-line tests 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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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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