MU20027 Applied Statistics I

Mathematical Institute in Opava
Winter 2020
Extent and Intensity
2/1/0. 3 credit(s). Type of Completion: zk (examination).
RNDr. Oldřich Stolín, Ph.D. (lecturer)
Guaranteed by
Mgr. Samuel Joshua Roth, Ph.D.
Mathematical Institute in Opava
Wed 13:05–14:40 BF - BrainFitness
  • Timetable of Seminar Groups:
MU20027/01: Wed 14:45–15:30 BF - BrainFitness, O. Stolín
Prerequisites (in Czech)
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
The course Applied Statistics consists of lectures and tutorials whose goal is to introduce students to Bayesian statistics and its practical methods.
  • 1. Randomness and probability.
    2. Probability and measure theory.
    3. Probability distributions.
    4. Random number generators.
    5. Markov chains.
    6. Metropolis-Hastings algorithm.
    7. Statistical models and dynamic updating. Confidence regions.
    8. The Bayes formula. Bayesian networks.
    9. Bayesian decision theory. Loss function, utility. Classical loss functions.
    10. Monte Carlo and MCMC
    required literature
  • A. Gelman, et. al. Bayesian Data Analysis, Third Edition. 2013. ISBN 1439840954. info
    recommended literature
  • Christian P. Robert. The Bayesian choice: From decision-theoretic foundations to computational implementation. New York, 2007. info
  • Christian P. Robert and George Casella. Monte Carlo statistical methods. New York, 2004. info
  • R. Hindls, S. Hronová, I. Novák. Metody statistické analýzy pro ekonomy. Praha, 2000. info
  • J.Ramík, Š. Čemerková. Statistika B. OPF SU, Karviná, 2000. info
  • J. Anděl. Statistické metody. Matfyzpress, 1993. info
  • J. Seger, R. Hindls. Statistické metody v ekonomii. H&H, 1993. info
  • L. Cyhelský. Úvod do teorie popisné statistiky. Praha, 1974. info
Language of instruction
Further comments (probably available only in Czech)
Study Materials
The course can also be completed outside the examination period.
Teacher's information
Conditions for course completion:
1. Satisfactory completion of all assignments with at most two exceptions. Assignments will be given each week during recitations. Students will have time in recitation to complete and submit the assignments in electronic format, usually in the form of a file containing data and calculations. Assignments not completed during recitation or for which the student is not present, may be completed during the week and submitted before the beginning of the next recitation.
2. A total of 60 points must be earned from the written tests. A student can earn at most 40 points from each individual test.
The course is also listed under the following terms Winter 2019.
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