Course unit code:
Course unit title:
Statistic and Optimization Methods
Mode of delivery, planned learning activities and teaching methods:
lecture – 1 hour weekly (on-site method)
seminar – 2 hours weekly (on-site method)
Credits allocated:
Recommended semester:
Environmental Protection Technologies – master (full-time, attendance method), 3. semester
Level of study:
Prerequisites for registration:
Assesment methods:
Students should work out their homework and to obtain at least 56% from the test.
Learning outcomes of the course unit:
Get acquainted students with the fundamentals of statistical methods, teach them to handle univariate and multivariate datasets with the assistance of statistical software.
Course contents:
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.
Language of instruction:
Slovak, English
Assessed students in total:

A 53.7 %

B 19.4 %

C 13.4 %

D 9 %

E 4.5 %

FX 0 %

Name of lecturer(s):
N. Krivoňáková, Z. Takáč (2023/2024 – Winter)
Z. Takáč (2022/2023 – Winter)
Z. Takáč (2021/2022 – Winter)
Z. Takáč (2020/2021 – Winter)
Z. Takáč (2019/2020 – Winter)
Z. Takáč (2018/2019 – Winter)
Z. Takáč (2017/2018 – Winter)
Z. Takáč (2016/2017 – Winter)
Z. Takáč (2015/2016 – Winter)
Course supervisor:
doc. RNDr. Zdenko Takáč, PhD.
Last modification:
19. 9. 2019

Department of Mathematics

AIS: 2023/2024   2021/2022   2019/2020   2018/2019   2017/2018  

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