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Data analysis methods

Summary

The aim of the subject is to introduce students to statistical analysis to the extent needed for processing measurements, data sets, and time series. After the successful completion of the course, students will be able to formulate questions which can be answered using data and, in order to do so, will become familiar with the principles of data collection, data processing, and relevant data presentation. Students will also learn to practically analyse time series using commonly used methods choosing the most suitable one for efficient analysis. Moreover, students will acquire skills needed for design and evaluation of inferences and predictions using data as well as assess the model suitability in the context of data processed.

Literature

BRIŠ, R. Probability and statistics for engineers. VŠB-TU Ostrava, 2011. https://homel.vsb.cz/~bri10/Teaching/Prob%20&%20Stat.pdf
SHUMWAY, R. H., STOFFER, D. S. Time Series Analysis and Its Applications: With R Examples. Springer, 4th ed. 2017. ISBN10 3319524518 

Advised literature

ŠKŇOUŘILOVÁ, P., BRIŠ, R. Statistics I, VŠB-TU Ostrava, Ostrava 2007. http://mdg.vsb.cz/portal/en/Statistics1.pdf
MARTINEZ, W. L. Exploratory data analysis with MATLAB. Boca Raton, Fla.: Champman&Hall/CRC, c2005. ISBN 1-58488-366-9 
KANTZ, H., SCHREIBER, T. Nonlinear Time Series Analysis, Cambridge University Press. 2nd ed. 2004. ISBN10 0521529026


Language of instruction čeština, angličtina
Code 230-0263
Abbreviation MAD
Course title Data analysis methods
Coordinating department Department of Mathematics
Course coordinator doc. Ing. Martin Čermák, Ph.D.