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Statistical Processing of Experimental Data

Statistical Processing of Experimental Data
639-0930/01
čeština Statistical Processing of Experimental Data
639-0930/02
čeština Statistical Processing of Experimental Data
639-0930/03
čeština Statistical Processing of Experimental Data
639-0930/04
čeština Statistical Processing of Experimental Data
639-0930/05
čeština Statistical Processing of Experimental Data
639-0930/06
čeština Statistical Processing of Experimental Data
639-0930/07
čeština Statistical Processing of Experimental Data
639-0930/08
čeština Statistical Processing of Experimental Data
639-0930/09
angličtina

Summary

The subject follows up on probability theory. It uses the tools of probability to present estimation of population parameters, hypothesis testing, modelling of technological processes with regression models and their assessment by correlation analysis. Multivariate regression is taught under the required theoretical conditions. Correlation analysis shows ways of measuring dependence for various types of variables.

Literature

KUTNER, M. H.,CH. J. NACHTSHEIM and J. NETER. Applied Linear Regression Models. NY:McGraw-Hill, 2004. ISBN 0-07-301344-7 .
BOX,G. E. P.,HUNTER,W.G.andHUNTER,J.S. Statistics for Experimenters.
NY: Wiley&Sons, 1978. ISBN 0-471-09315-7 .
JAMES, G., D. WITTEN, T. HASTIE a R. TIBSHIRANI. An Introductuion to Statistical Learning. NY: Springer, 2013. ISBN 978-1-4614-7138-7 .
DRAPER, N. R. and H. SMITH. Applied Regression Analysis. NY: Wiley, 1998. ISBN 978-0471170822 .
RYAN, T. P. Modern Regression Methods. NY: Wiley, 2008. ISBN 978-0470550441 .

Advised literature

MONTGOMERY, D. C. Applied Statistics and Probability for Engineers. NY: Wiley, 2010. ISBN-13 978-1-1185-3971-2 .
SHESKIN, D. J. Handbook of Parametric and Nonparametric Statistical Procedures. NY: Chapman and Hall, 2003. ISBN 1-58488-440-1 .


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Language of instruction čeština, čeština, čeština, čeština, čeština, čeština, čeština, čeština, angličtina
Code 639-0930
Abbreviation SZED
Course title Statistical Processing of Experimental Data
Coordinating department Department of Quality Management
Course coordinator Ing. Filip Tošenovský, Ph.D.