Gurantor department | Department of Applied Mathematics | Credits | 7 |

Subject guarantor | Ing. Jan Kracík, Ph.D. | Subject version guarantor | Ing. Jan Kracík, Ph.D. |

Study level | undergraduate or graduate | Requirement | Compulsory |

Year | 2 | Semester | winter |

Study language | Czech | ||

Year of introduction | 2019/2020 | Year of cancellation | |

Intended for the faculties | FEI | Intended for study types | Bachelor |

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

Login | Name | Tuitor | Teacher giving lectures |

KRA0220 | Ing. Jan Kracík, Ph.D. |

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

Form of study | Way of compl. | Extent |

Full-time | Credit and Examination | 3+2 |

Part-time | Credit and Examination | 12+8 |

Students will understand basic concepts and relations in probability theory needed for mathematical statistics.

Lectures

Tutorials

Project work

Probability theory provides a framework for treating uncertainty and is a foundation for mathematical statistics. Students will gain knowledge of fundamental notions of probability theory at a level not requiring knowledge of measure theory.

RAO, C. RADHAKRISHNA. Linear statistical inference and its applications. 2. ed., paperback ed. New York: Wiley, 2002. ISBN 0471218758.

TEETOR, Paul. R cookbook. Sebastopol, CA: O'Reilly, 2011. ISBN 9780596809157

2 tests per during the semester
semestral project

There are not defined other requirements for student.

Subject has no prerequisities.

Subject has no co-requisities.

Lectures:
Probability space
Conditional probability, independent random events, law of total probability, Bayes' theorem
Conditional independence of random events
Random variable, probability distribution, numerical characteristics
Selected discrete distributions
Selected continuous distributions
Multivariate random variable, probability distribution, numerical characteristics
Independece of random variables, conditional independence
Multivariate normal distribution
Convergence of random variables
Limit theorems
Transformations of random variables, sum of random variables, sampling
Excercises will follow the content of the lectures. During the excercises students will learn basics of R language.

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 | 30 | 10 |

Examination | Examination | 70 | 35 |

Show history

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

2020/2021 | (B0541A170008) Computational and Applied Mathematics | VMI | P | Czech | Ostrava | 2 | Compulsory | study plan | ||||

2020/2021 | (B0541A170008) Computational and Applied Mathematics | VMI | K | Czech | Ostrava | 2 | Compulsory | study plan | ||||

2019/2020 | (B0541A170008) Computational and Applied Mathematics | VMI | P | Czech | Ostrava | 2 | Compulsory | study plan | ||||

2019/2020 | (B0541A170008) Computational and Applied Mathematics | VMI | K | Czech | Ostrava | 2 | Compulsory | study plan |

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