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« one step back EDUCATION

Statistical Data Analysis (N445057SIS)

Lecture Exercise Laboratory Examination Credits
2 2 0 Z+Zk 5
Guarantor Svozil Daniel, Spiwok Vojtěch
Teacher Svozil Daniel, Spiwok Vojtěch


This course is the follow-up to the Applied Statistics lectures. Freely available statistical software R is presented, and students use it to practise common statistical tasks such as, e.g., exploratory data analysis, hypothesis testing, analysis of variance or regression.


  1. Introduction to R statistics software, help
  2. Input and output in R
  3. Creating graphs in R
  4. Basic statistic distributions, random numbers in R
  5. Descriptive one-dimensional statistics, boxplot
  6. Standard deviation, mean error, confidence interval and their graphic representation in R
  7. Hypotheses testing in R: t-test
  8. Hypotheses testing in R: variance analysis
  9. Descriptive statistics and their use in R
  10. Creating and testing linear models in R
  11. Creating and testing non-linear models in R
  12. Basic linear algebra in R
  13. Principal component analysis, its implementation and use in R
  14. Cluster analysis in R


  • online course materials at
  • video course "Computing for Data Analysis" (using and programming in R) by Roger D. Peng,
  • video course "Data Analysis" (applied statistics in R) by Jeff Leek,
  • online textbook OpenIntro Statistics -
  • online textbook OnlineStatBook -
  • online textbook Hyperstat -
  • online textbook StatPrimer -
  • textbook Venables R.W.N., Smith D.M. and the R Core Team: An Introduction to R (available online na, 20.5.2013)
  • textbook Cohen T., Cohen J.Y.: Statistics and Data with R: An applied approach through examples. ISBN: 9780470721896 (online available from domain at, 20.5.2013)
  • textbook Rumsey D. Intermediate Statistics for Dummies; For Dummies, 2007. ISBN 0470045205


  • Credit exam in the middle of term, written test at the end of term.