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Advanced Statistics for Bioinformatics

Summary

The course will emphasize methods of applied statistics and data analysis. Theoretical considerations will be included to the extent that knowledge of theory is necessary for a sound understanding of methods and contributes to the development of data analysis skills and the ability to interpret results of statistical analysis. Topics are included in the syllabus below.

Literature

• BRIŠ, Radim. Probability and Statistics for Engineers. Ostrava, 2011. Available at: http://homel.vsb.cz/~bri10/Teaching/Prob%20&%20Stat.pdf
• JOHNSON, James L. Probability and statistics for computer science. Hoboken, NJ: Wiley Interscience, 2008. ISBN 978-0470383421 .
• VAN BELLE, Gerald a Lloyd FISHER. Biostatistics: a methodology for the health sciences. 2nd ed. Hoboken, NJ: John Wiley, 2004. ISBN 0471031852.

Advised literature

• HASTIE, Trevor, Robert TIBSHIRANI a J. H FRIEDMAN. The elements of statistical learning: data mining, inference, and prediction. 2nd ed. New York, NY: Springer, 2009. ISBN 9780387848570.
• JAMES, Gareth, Daniela WITTEN, Trevor HASTIE a Robert TIBSHIRANI. An introduction to statistical learning: with applications in R. New York: Springer, [2013]. Springer texts in statistics, 103. ISBN 978-1-4614-7138-7 .
• MOORE, Dirk F. Applied survival analysis using R. New York, NY: Springer Science+Business Media, 2016. ISBN 978-3319312439 .
• TUTZ, Gerhard. Regression for categorical data. New York: Cambridge University Press, 2012. ISBN 9781107009653 .
• HOSMER, David W a Stanley LEMESHOW. Applied logistic regression. 2nd ed. New York: Wiley, 2000. ISBN 978-0471-35632-8 .
• MÜLLER, Peter, Fernando Andres QUINTANA, Alejandro JARA a Tim HANSON. Bayesian Nonparametric Data Analysis. Springer, 2015. ISBN 978-3319189673 .


Language of instruction čeština, angličtina
Code 470-6406
Abbreviation PSB
Course title Advanced Statistics for Bioinformatics
Coordinating department Department of Applied Mathematics
Course coordinator prof. Ing. Radim Briš, CSc.