SubjectsSubjects(version: 953)
Course, academic year 2023/2024
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Advanced aspects of R environment - NMST547
Title: Pokročilé aspekty prostředí R
Guaranteed by: Department of Probability and Mathematical Statistics (32-KPMS)
Faculty: Faculty of Mathematics and Physics
Actual: from 2023 to 2023
Semester: winter
E-Credits: 3
Hours per week, examination: winter s.:0/2, C [HT]
Capacity: unlimited
Min. number of students: unlimited
4EU+: no
Virtual mobility / capacity: no
State of the course: taught
Language: Czech
Teaching methods: full-time
Teaching methods: full-time
Additional information: http://msekce.karlin.mff.cuni.cz/~komarek/vyuka/nmst440.html
Guarantor: doc. RNDr. Arnošt Komárek, Ph.D.
Class: M Mgr. PMSE
M Mgr. PMSE > Povinně volitelné
Classification: Informatics > Software Applications
Mathematics > Probability and Statistics
Pre-requisite : {At least one courses in GLM}
Incompatibility : NMST440
Annotation -
Advanced aspects of R, a free software environment for statistical computation and graphics, basics of C programming, use of computational clusters for extensive computation.
Last update: Omelka Marek, doc. Ing., Ph.D. (03.12.2020)
Aim of the course -

To teach students to use effectively advanced tools of R, a free software environment for statistical computation and graphics, related open-source software products and other selected computational tools.

Last update: Komárek Arnošt, doc. RNDr., Ph.D. (03.12.2020)
Course completion requirements -

The course credit will be awarded to the student who hands in a satisfactory solution to each assignment by the prescribed deadline. The nature of these requirements precludes any possibility of additional attempts to obtain the exercise class credit.

Last update: Omelka Marek, doc. Ing., Ph.D. (30.11.2020)
Literature -

Chambers, J. M. Software for Data Analysis: Programming with R. New York: Springer-Verlag, 2008, xiv + 500 s. ISBN: 978-0-387-75935-7.

Murrell, P. R Graphics, Second Edition. Boca Raton: Chapman & Hall/CRC, 2012, xxvii + 518 s. ISBN: 978-1-4398-3177-9.

Last update: Komárek Arnošt, doc. RNDr., Ph.D. (03.12.2020)
Teaching methods -

Seminar + individual work with possibility of advice.

Last update: Omelka Marek, doc. Ing., Ph.D. (30.11.2020)
Syllabus -

1. R programming (functions, vectorized operations, ...).

2. Advanced graphics in R (lattice, ggplot2, ...).

3. Automatized reporting using R, systems for automatized reporting and preparation of presentations (Sweave, markdown, shiny).

4. Basics of a programming language C, use for computationally intensive computation when integrated with the R environment.

5. Use of computational clusters for intensive computation.

Last update: Komárek Arnošt, doc. RNDr., Ph.D. (03.12.2020)
Entry requirements -
  • Foundations of statistical inference (statistical test, confidence interval, standard error, consistency);
  • Basic procedures of statistical inference (asymptotic tests on expected value, one- and two-sample t-test, one-way analysis of variance, chi-square test of independence);
  • Linear model;
  • Intermediate knowledge of R, a free software environment for statistical computing and graphics (https://www.r-project.org);
  • Working knowledge of LaTeX;
  • Ability of algorithmic programming (in arbitrary language, e.g., Python, Pascal, C/C++, Fortran, ...).

Last update: Omelka Marek, doc. Ing., Ph.D. (30.11.2020)
 
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