Course details

Statistics, Stochastic Procesess, Operational Analysis

DMA1 FEEC BUT DMA1 Acad. year 2015/2016 Winter semester

Current academic year

Basic statistical tests, i.e. t-test, F-test, chi-quadrant test. Regression analysis. Goodness of fit test. Nonparametric tests. Mathematical methods in economics - linear programming, the transport problem. Dynamic programming, inventory models. Markov chain and time series.


Language of instruction



Examination (oral)

Time span

39 hrs lectures

Assessment points

100 exam



Subject specific learning outcomes and competences

The graduate of this course should be able to solve the optimizing and statistical problems of technical and economical practice.

Learning objectives

The objective of the course is to expand knowledge in the area of statistical tests and data sample processing, Markov chain and time series, including applications in economy.

Fundamental literature

  • Zapletal, J.: Úvod do analýzy ekonomických časových řad. PC-DIR, VUT, Brno 2000.
  • Zapletal, J.: Základy počtu pravděpodobnosti a matematrické statistiky. PC-DIR,VUT, Brno, 1995
  • Anděl, J.: Statistické metody. Matfyzpress, MFF UK Praha, 1993.
  • Taha, H.A.: Operations research. An Introduction. Fourth Edition, Macmillan Publishing Company, New York 1989.
  • Miller, I., Miller, M.: John E. Freund's Mathematical Statistics. Sixth Edition. Prentice Hall, Inc., New Jersey 1999. Předchozí vydání publikováno pod názvem Freund, J.E.: Mathematical Statistics, Fifth Edition.
  • Montgomery, D.C., Runger, G.C.: Applied Statistics and Probability for Engineers. Third Edition. John Wiley & Sons, Inc., New York 2003.
  • Loftus, J., Loftus, E.: Essence of Statistics. Second Edition, A. A. Knopf, New York, 1988
  • Aramanovič, J. G., Lunc, G. L., Elsgolc, L. C., Funkcie komplexnej premennej, operátorový počet, teória stability, Alfa, SNTL, 1973.

Syllabus of lectures

  1. Basic concepts of probability theory
  2. Statistical samples
  3. Point and interval estimates
  4. Testing hypotheses of given parameters (not only normal distribution)
  5. Distribution tests (chi-quadrant test, Kolmogorov-Smirnov test, etc.)
  6. Operational analysis methods, linear and non-linear programming
  7. Dynamical programming, Bellman principle
  8. Markov chain, M/M/s systems
  9. Inventory models, especially random issues
  10. Replicate theory, deterministic and especially stochastic problems.
  11. Time series
  12. Note on floating averages and hidden periods

Course inclusion in study plans

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