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Obnovit | RAW

Statistical Data Analysis

Lecture Excercise/laboratory
2019, Summer Semester
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Credits 5
Hours per week 2 / 2 / 0
Examination C+Ex
Study Language Czech
Level []
Guarantor doc. Ing. Vojtěch Spiwok, Ph.D.
doc. Mgr. Daniel Svozil, Ph.D.
Supplemental electronic materials available at UCT Prague's e-learning

Summary

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.

Syllabus

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

Literature

R:Venables R.W.N., Smith D.M. and the R Core Team: An Introduction to R (available online na http://cran.r-project.org/doc/manuals/r-release/R-intro.pdf, 20.5.2013)
R:Cohen T., Cohen J.Y.: Statistics and Data with R: An applied approach through examples. ISBN: 9780470721896 (online available from vscht.cz domain at http://onlinelibrary.wiley.com/book/10.1002/9780470721896, 20.5.2013)
A:Rumsey D. Intermediate Statistics for Dummies; For Dummies, 2007. ISBN 0470045205

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