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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
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

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Annotation -

Last update: doc. Ing. Marek Omelka, Ph.D. (03.12.2020)

Advanced aspects of R, a free software environment for statistical computation and graphics, basics of C programming, use of computational clusters for extensive computation.

Aim of the course -

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

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.

Course completion requirements -

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

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.

Literature -

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

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.

Teaching methods -

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

Seminar + individual work with possibility of advice.

Syllabus -

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

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.

Entry requirements -

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

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, ...).