Subject description
Introduction to R
- Data structures and objects
- R packages
- Use and design of functions, control structures
- Elements of statistical graphics
- Functions for statistical tests and models
- Design of R packages
Data visualization and exploratory data analysis
Principles of stochastic simulations, randomization and permutation tests
Reproducible research
- Reporting with markdown and LaTeX: elements and use
knitr – connecting R and markdown/LaTeX to make reproducible computer supported statistical reports and presentations
The subject is taught in programs
Objectives and competences
Statistical anlysts need to be comfortable with state-of-the art computer tools which enable efficient data organization, visualization, exploratory and model analysis, and preparation of reproducible reports. Students will gain fundamental knowledge and skills to use statistical development platform R and combine it with LaTeX and Sweave. This will be useful in all other subjects and practical work which requires preparation of technically advanced statistical reports.
Teaching and learning methods
Lectures, Lab work, home work, seminar
| Part of the pedagogical process will be carried out with the help of ICT technologies and the opportunities they offer. |
Expected study results
Knowledge and understanding of statistical development platform R and document preparation system LaTeX.
Basic sources and literature
Crawley M (2009). The R Book. Wiley,ISBN 0470510242.
Venables W.N. in B. D. Ripley (2002). Modern Applied Statistics with S. Fourth Edition, Springer. ISBN 0-387-95457-0.
Teetor P (2011). R Cookbook. O'Reilly ISBN 0596809158.
R Development Core Team (2009). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL http://www.R-project.org.
Razpoložljiva literatura se letno spreminja in posodablja. Primerni viri so zbrani na spletni strani www.r-project.org, zato se bodo aktualni viri letno spreminjali.
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