Get acquainted students with the fundamentals of statistical methods, teach them to handle univariate and multivariate datasets with the assistance of statistical software.
Prerequisites for registration:
The subject is divided into two parts. In the first part, there are discussed the theoretical
foundations of applied statistics, especially probability, random variables and random vectors.
The second part is devoted to the basic statistical analysis (statistical analysis of one-dimensional data sets, statistical analysis of multidimensional data sets ). One of these analysis is theory of estimations, expressly point and interval estimations of unknown parameters in the models of direct measurements and indirect measurements. Next analysis is testing of statistical hypotheses, tangibly testing of a good concordance data sets and models, testing of expectations of the normal and exponential distributions.
Recommended or required reading:
VARGA, Š. Matematická štatistika. Bratsilava : Nakladateľstvo STU, 2012. 219 s. ISBN 978-80-227-3789-0.
VOLAUF, P. Matematická štatistika: Zbierka príkladov. Bratislava : STU v Bratislave, 2001. 166 s. ISBN 80-227-1523-9.
MONTGOMERY, D C. – RUNGER, G C. Applied Statistics and Probability for Engineers. New York : John Wiley & Sons, 2002. 706 s. ISBN 0-471-20454-4.
VARGA, Š. – ŠABO, M. – POSPÍCHAL, J. Matematika III: Matematická štatistika a numerické metódy. Bratislava : STU v Bratislave FCHPT, 2003. 202 s. ISBN 80-227-1840-8.
ROUSSAS, G G. A course in mathematical statistics. San Diego : Academic Press, 1997. 572 s. ISBN 0-12-599315-3.
Planned learning activities and teaching methods:
The subject is divided into lectures and exercises, the computers and the necessary software are available.
Assesment methods and criteria:
Students can obtain 50 points from their homework during the semester, and 50 points from the closing test. Evaluation: A (92-100 points), B (83-91 points), C (74-82 points), D (65-73 points), E (56-64 points), Fx (0-55 points).
Language of instruction:
Institute of Information Engineering, Automation and Mathematics was established in 1.1.2006 from two departments: Department of Information Engineering and Process Control and Department of Mathematics.