SubjectsSubjects(version: 853)
Course, academic year 2019/2020
  
Statistical Data Analysis - M143002
Title: Statistická analýza dat
Guaranteed by: Department of Informatics and Chemistry (143)
Actual: from 2019
Semester: winter
Points: winter s.:5
E-Credits: winter s.:5
Examination process: winter s.:
Hours per week, examination: winter s.:2/2 C+Ex [hours/week]
Capacity: unlimited / unlimited (unknown)
Min. number of students: unlimited
Language: Czech
Teaching methods: full-time
Level:  
For type: Master's (post-Bachelor)
Note: course can be enrolled in outside the study plan
enabled for web enrollment
Guarantor: Svozil Daniel doc. Mgr. Ph.D.
Interchangeability : N143042
Annotation -
Last update: Hladíková Jana (04.01.2018)
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.
Aim of the course -
Last update: Hladíková Jana (04.01.2018)

Students will be able to:

Use the R software (environment for statistical computing)

Do the exploratory analysis and hypotheses testing in R

Do the regression analysis in R

Analyze multidimensional data in R

Present results of statistics analysis using graphical capabilities of R

Literature -
Last update: Svozil Daniel doc. Mgr. Ph.D. (31.10.2018)

R:Statisticka analýza dat v R, Vojtech Spiwok, 2015. available at https://web.vscht.cz/~spiwokv/statistika/skripta.pdf

R:Pekár, S., Moderní analýza bioologických dat, Scientia, 2009, ISBN 978-80-86960-44-9.

Z:Konečná, K., Koláček, J., Jak pracovat s jazykem R. 2014. PřF MU Brno (available at https://www.math.muni.cz/~kolacek/vyuka/vypsyst/navod_R.pdf)

A:Venables R.W.N., Smith D.M. and the R Core Team: An Introduction to R. 2018. (available at http://cran.r-project.org/doc/manuals/r-release/R-intro.pdf)

A:Cohen T., Cohen J.Y.: Statistics and Data with R: An applied approach through examples. 2008. ISBN: 9780470721896

A:Rumsey D. Intermediate Statistics for Dummies; For Dummies, 2007. ISBN 0470045205

Learning resources -
Last update: Hladíková Jana (04.01.2018)

Online course materials at http://e-learning.vscht.cz

video course "Computing for Data Analysis" (using and programming in R) by Roger D. Peng, https://www.coursera.org/course/compdata

video course "Data Analysis" (applied statistics in R) by Jeff Leek, https://www.coursera.org/course/dataanalysis

Online textbooks

OpenIntro Statistics - http://www.openintro.org/stat/index.php

OnlineStatBook - http://onlinestatbook.com/2/index.html

Hyperstat - http://davidmlane.com/hyperstat/index.html

StatPrimer - http://www.sjsu.edu/faculty/gerstman/StatPrimer/

Requirements to the exam - Czech
Last update: Svozil Daniel doc. Mgr. Ph.D. (31.01.2018)

Zápočet je udělen na základě vypracování individuálního projektu. Závěrečná zkouška je písemná.

Syllabus -
Last update: Hladíková Jana (04.01.2018)

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

Registration requirements -
Last update: Hladíková Jana (04.01.2018)

Mathematics, Applied Statistics

Course completion requirements -
Last update: Svozil Daniel doc. Mgr. Ph.D. (31.01.2018)

The credit is given on the completion of an individual project. The final exam is written.

Teaching methods
Activity Credits Hours
Účast na přednáškách 1 28
Příprava na přednášky, semináře, laboratoře, exkurzi nebo praxi 1 28
Práce na individuálním projektu 1 28
Příprava na zkoušku a její absolvování 1 28
Účast na seminářích 1 28
5 / 5 140 / 140
Coursework assessment
Form Significance
Examination test 70
Continuous assessment of study performance and course -credit tests 30

 
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