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Lecturer(s)
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Šmajserová Veronika, Mgr.
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Czolková Adéla, Bc.
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Chupáň Tomáš, Mgr.
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Fišerová Eva, doc. RNDr. Ph.D.
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Pavlů Ivana, Mgr. Ph.D.
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Fačevicová Kamila, Mgr. Ph.D.
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Bebčáková Iveta, Mgr. Ph.D.
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Ženčák Pavel, RNDr. Ph.D.
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Jašková Paulína, Mgr.
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Course content
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1. Introduction to the R software and RStudio environment 2. Types of objects in R 3. Import of data in R, its manipulation and saving 4. If, for and while loops 5. Creating of own R functions 6. Data visualisation 7. Other related topics
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Learning activities and teaching methods
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Dialogic Lecture (Discussion, Dialog, Brainstorming), Demonstration
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Learning outcomes
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Introduction to the stastistical software R. The main focus is given on manipulation with different types of datasets, its uploading, modification and visualisation. The second part of the course is dedicated to the basics of programming in R.
Basic knowledge of R language.
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Prerequisites
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Basic knowledge of working with PC.
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Assessment methods and criteria
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Student performance
Active participation in seminars, work on given individual tasks and homeworks.
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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. (2011). The Art of R Programming. No Starch Press.
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P. Teetor. R Cookbook. (2011). Prooven Recipes for Data Analysis, Statistics, and Graphics. O?Reilly Media, Inc.
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Venables, W. N., Smith, D. M. (2019). R Core Team. An Introduction to R. R Foundation for Statistical Computing. Vienna, Austria.
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Verzani, J. SimpleR - Using R for Introductory Statistics.
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Wickham, H., Grolemund, G. (2017). R for Data Science. O?Reilly Media, Inc.
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