| Course Unit Code | 470-4405/02 |
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| Number of ECTS Credits Allocated | 6 ECTS credits |
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| Type of Course Unit * | Optional |
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| Level of Course Unit * | Second Cycle |
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| Year of Study * | |
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| Semester when the Course Unit is delivered | Winter, Summer Semester |
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| Mode of Delivery | Face-to-face |
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| Language of Instruction | English |
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| Prerequisites and Co-Requisites | Course succeeds to compulsory courses of previous semester |
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| Name of Lecturer(s) | Personal ID | Name |
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| BRI10 | prof. Ing. Radim Briš, CSc. |
| LIT40 | Ing. Martina Litschmannová, Ph.D. |
| Summary |
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| Students will be able to define basic concepts of probability, describe statistical methods, and explain their significance. They will apply statistical techniques and procedures to analyze data and interpret the results. The course will also develop students' skills to analyze and critically evaluate statistical information, as well as to propose appropriate methods for solving practical problems in probability and statistics. |
| Learning Outcomes of the Course Unit |
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| The course aims to enable students to acquire knowledge of probability theory and applied statistics and to demonstrate the ability to use this knowledge practically. |
| Course Contents |
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1) Introduction to Probability Theory
2) Discrete random variable
3) Selected distributions of discrete random variables
4) Continuous random variable
5) Selected distributions of continuous random variables
6) Limit Theorems
7) Random Vector
8) Introduction to statistics, exploratory analysis
9) The survey, random sampling and basic sample characteristics
10) Introduction to estimation theory
11) Introduction to hypothesis testing (principle)
12) Hypotheses testing - mean, probability, variance (one-sample and two-sample tests)
13) Analysis of variance (verification normality, ANOVA and Kruskal-Wallis test)
14) Non-Parametric Hypothesis Tests |
| Recommended or Required Reading |
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| Required Reading: |
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BERTSEKAS, Dimitri P. a TSISIKLIS, John N. Introduction to probability. Second edition. Nashua, NH: Athena Scientific, [2008]. ISBN 978-1886529236.
JAMES, Gareth; WITTEN, Daniela; HASTIE, Trevor a TIBSHIRANI, Robert. An introduction to statistical learning: with applications in R. Second edition. Springer texts in statistics. New York: Springer, [2021]. ISBN 978-1071614174.
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LITSCHMANNOVÁ, Martina. Vybrané kapitoly z pravděpodobnosti. Online. VŠB-TUO, 2011. Dostupné z: http://mi21.vsb.cz/modul/vybrane-kapitoly-z-pravdepodobnosti.
LITSCHMANNOVÁ, Martina. Úvod do statistiky. Online. VŠB-TUO, 2011. Dostupné z: https://mi21.vsb.cz/modul/uvod-do-statistiky.
ANDĚL, Jiří. Základy matematické statistiky. Vyd. 3. Praha: Matfyzpress, 2011. ISBN 978-80-7378-162-0.
JAMES, Gareth; WITTEN, Daniela; HASTIE, Trevor a TIBSHIRANI, Robert. An introduction to statistical learning: with applications in R. Second edition. Springer texts in statistics. New York: Springer, [2021]. ISBN 978-1071614174. |
| Recommended Reading: |
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| WHEELAN, Charles. Naked Statistics: Stripping the Dread from the Data. W. W. Norton & Company, 2014. ISBN 978-0393347777. |
ANDĚL, Jiří. Statistické metody. Páté vydání. Praha: Matfyzpress, 2019. ISBN 978-80-7378-381-5.
FRIEDRICH, Václav. Statistika 1: vysokoškolská učebnice pro distanční studium. Plzeň: Západočeská univerzita, 2002. ISBN 80-7082-913-3.
BRUCE, Peter; BRUCE, Andrew a GEDECK, Peter. Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python. 2. O'Reilly Media, 2020. ISBN 978-1492072942. |
| Planned learning activities and teaching methods |
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| Lectures, Tutorials |
| Assesment methods and criteria |
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| Tasks are not Defined |