Gurantor department | Department of Applied Mathematics | Credits | 4 |

Subject guarantor | Ing. Martina Litschmannová, Ph.D. | Subject version guarantor | Ing. Martina Litschmannová, Ph.D. |

Study level | undergraduate or graduate | Requirement | Choice-compulsory |

Year | 1 | Semester | summer |

Study language | Czech | ||

Year of introduction | 2016/2017 | Year of cancellation | 2020/2021 |

Intended for the faculties | USP | Intended for study types | Follow-up Master |

Instruction secured by | |||
---|---|---|---|

Login | Name | Tuitor | Teacher giving lectures |

KRA0220 | Ing. Jan Kracík, Ph.D. | ||

LIT40 | Ing. Martina Litschmannová, Ph.D. |

Extent of instruction for forms of study | ||
---|---|---|

Form of study | Way of compl. | Extent |

Full-time | Credit and Examination | 3+3 |

Part-time | Credit and Examination | 10+10 |

The course is designed for graduates to gain an initial idea of the basic concepts and tasks that fall within the field of probability and statistics and were able to apply their knowledge in practice.

Lectures

Tutorials

This is an introductory course in statistics. The course will emphasize methods of applied statistics and data analysis. Theoretical considerations will be included to the extent that knowledge of theory is necessary for a sound understanding of methods and contributes to the development of data analysis skills and the ability to interpret results of statistical analysis. The objective of the course is to develop sufficient knowledge of statistical tools and procedures, understanding of the underlying theory on which the procedures are based, and facility in the application of statistical tools to enable the student to incorporate sound statistical methodology into other areas of his or her own work.

Briš, R. (2011), Probability and Statistics for Engineers, VŠB-TU Ostrava, WEB: https://homel.vsb.cz/~bri10/Teaching/Prob%20&%20Stat.pdf
DUMMER, R.M. (1998), Introduction to Statistical Science, VŠB-TU Ostrava, ISBN 80-7078-497-0
StatSoft, Inc. (2013). Electronic Statistics Textbook. Tulsa, OK: StatSoft. WEB: https://statisticasoftware.wordpress.com/2012/04/12/electronic-statistics-textbook/
HILL, T. & LEWICKI, P. (2007). STATISTICS: Methods and Applications. StatSoft, Tulsa, OK.

Triola, M. F. (2008). Elementary statistics with multimedia study guide. Boston: Pearson Addison Wesley. ISBN 978-0321460929.
DALGAARD, P. (2008). Introductory statistics with R. 2nd ed. New York, NY: Springer. Statistics and computing. ISBN 978-0-387-79053-4.
Rosling, H., Rosling, O., & Rönnlund, A. R. (2019). Factfulness: ten reasons we’re wrong about the world - and why things are better than you think. Sceptre. ISBN 9781473637474.
Darrell Huff, (1954) How to Lie with Statistics (illust. I. Geis), Norton, New York, ISBN 0-393-31072-8.

Presence form:
Discussions:
- 10 short tests during the semester per 2 points, 20 points overall (minimum required: 6 points)
- 4 homeworks per 5 points, 20 points overall (minimum required: 5 points for each task)
Exam:
- 10 short tests during the semester per 2 points, 20 points overall (minimum required: 6 points)
Combined form:
Discussions:
- 3 homeworks during the semester per 10 points, for a total maximum of 30 points (minimum required: 3 points for each homework)
- Test with a maximum of 10 points (minimum required: 1 point)
- Semester project, max 20 points (minimum required: 10 points)
Exam:
- written exam (practical part: max. 50 points, required minimum: 25 points, theoretical part: max. 10 points, required minimum: 2 points)
For successful completion of the Discussions is given credit. Students will receive credit if they meet the required
minimum of each of the sub-tasks and compensatory gain at least 20 points.
Students will pass the exam if they meet the the required minimum of each of the sub-tasks and compensatory gain (Discussions and Exam) at least 51 points.

Presence form: Active participation in at least 80% of discussions.

Subject has no prerequisities.

Subject has no co-requisities.

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)

Task name | Type of task | Max. number of points
(act. for subtasks) | Min. number of points |
---|---|---|---|

Credit and Examination | Credit and Examination | 100 (100) | 51 |

Credit | Credit | 40 (40) | 20 |

Průběžné testy | Written test | 20 | 6 |

Domácí úkoly | Other task type | 20 | 10 |

Aktivní účast | Other task type | ||

Examination | Examination | 60 (60) | 27 |

Praktická část | Written examination | 50 | 25 |

Teoretická část | Written examination | 10 | 2 |

Show history

Academic year | Programme | Field of study | Spec. | Zaměření | Form | Study language | Tut. centre | Year | W | S | Type of duty | |
---|---|---|---|---|---|---|---|---|---|---|---|---|

2018/2019 | (N2658) Computational Sciences | (2612T078) Computational Sciences | P | Czech | Ostrava | 1 | Choice-compulsory | study plan | ||||

2017/2018 | (N2658) Computational Sciences | (2612T078) Computational Sciences | P | Czech | Ostrava | 1 | Choice-compulsory | study plan | ||||

2016/2017 | (N2658) Computational Sciences | (2612T078) Computational Sciences | P | Czech | Ostrava | 1 | Choice-compulsory | study plan |

Block name | Academic year | Form of study | Study language | Year | W | S | Type of block | Block owner |
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