Course: Statistical Software

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Course title Statistical Software
Course code KAP/SSO
Organizational form of instruction Lecture + Lesson
Level of course Master
Year of study not specified
Semester Summer
Number of ECTS credits 4
Language of instruction Czech
Status of course Compulsory-optional
Form of instruction Face-to-face
Work placements Course does not contain work placement
Recommended optional programme components None
Course availability The course is available to visiting students
Lecturer(s)
  • Schindler Martin, Mgr. Ph.D.
Course content
lectures and practicals: 1. Environment of statistical software R and RStudio. 2. Data import and export, data manipulation. 3. Syntax, programming in R. 4. Functions, loops, conditional statements. 5. Summaries and graphical outputs in R, RMarkdown. 6. Basic data structures and work with them. 7. Data manipulation, transformation and selection. 8. Descriptive statistics of one-dimensional data, boxplot, histogram. 9. Descriptive statistics of multidimensional data; scatterplot diagram, correlation. 10. Basics of probability distributions, generating of random numbers. 11. Calculation and graphical display of confidence intervals. 12. Hypotheses testing of location parameter, t-tests and their nonparametric alternatives. 13. Analysis of variance, verification of the assumptions. 14. Regression models, regression diagnostics.

Learning activities and teaching methods
Monological explanation (lecture, presentation,briefing)
  • Class attendance - 42 hours per semester
  • Preparation for exam - 106 hours per semester
Learning outcomes
Students will familiarize with the basic concepts of the statistical software R and its extensions in order to learn the basic programming technics and basics of statistical analysis in R.
Basic knowledge of programming technics and statistical analysis in R.
Prerequisites
Elements of probability theory, data analysis and statistics.

Assessment methods and criteria
Oral exam, Written exam

work at the practicals, semestral work/final test
Recommended literature
  • Anděl, J. Statistické metody. Matfyzpress: Praha, 2007. ISBN 978-80-7378-003-6.
  • Dalgaard, P. Introductory Statistics with R. 2008. ISBN 978-0-387-79053-4.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester