Gurantor department | Department of Applied Mathematics | Credits | 6 |

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

Study level | undergraduate or graduate | Requirement | Optional |

Year | 1 | Semester | summer |

Study language | Czech | ||

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

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

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

Login | Name | Tuitor | Teacher giving lectures |

KRA0220 | Ing. Jan Kracík, Ph.D. | ||

KRA04 | Mgr. Bohumil Krajc, Ph.D. |

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

Form of study | Way of compl. | Extent |

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

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

Students will understand basic concepts of probability theory, mathematical statistics and numerical methods.

Lectures

Tutorials

Project work

The subject is intended for students of master's program Computational and applied mathematics without background in mathematical statistics and numerical methods.

RAO, C. RADHAKRISHNA. Linear statistical inference and its applications. 2. ed., paperback ed. New York: Wiley, 2002. ISBN 0471218758.
Quarteroni, R. Sacco, F. Saleri, Numerical Mathematics. Springer, 2007.

TEETOR, Paul. R cookbook. Sebastopol, CA: O'Reilly, 2011. ISBN 9780596809157
W.H. Press, B.P. Flannery, S.A. Teukolski, W.T. Vetterling, Numerical Recipes in C. Cambridge University Press, 19

semestral project, test
written and oral exam

No additional requirements are imposed on the student.

Subject has no prerequisities.

Subject has no co-requisities.

Probability theory:
Probability space
Random variable, random vector
Selected probability distributions
Limit theorems
Mathematical statistics:
Independent random samples
Hypothesis tests
Statistical estimation
Analysis of variance
Linear regression
Numerical methods:
Data fitting
Numerical integration
Iterative methods for solution of nonlinear equations
Numerical solution to ordinary differential equations

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 (30) | 10 |

Projekt | Project | 10 | 5 |

Zápočtová písemka | Written test | 20 | 5 |

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 | (N0541A170007) Computational and Applied Mathematics | (S01) Applied Mathematics | K | Czech | Ostrava | 1 | Optional | study plan | ||||

2020/2021 | (N0541A170007) Computational and Applied Mathematics | (S02) Computational Methods and HPC | P | Czech | Ostrava | 1 | Optional | study plan | ||||

2020/2021 | (N0541A170007) Computational and Applied Mathematics | (S01) Applied Mathematics | P | Czech | Ostrava | 1 | Optional | study plan | ||||

2020/2021 | (N0541A170007) Computational and Applied Mathematics | (S02) Computational Methods and HPC | K | Czech | Ostrava | 1 | Optional | study plan | ||||

2019/2020 | (N0541A170007) Computational and Applied Mathematics | (S01) Applied Mathematics | P | Czech | Ostrava | 1 | Optional | study plan | ||||

2019/2020 | (N0541A170007) Computational and Applied Mathematics | (S02) Computational Methods and HPC | P | Czech | Ostrava | 1 | Optional | study plan | ||||

2019/2020 | (N0541A170007) Computational and Applied Mathematics | (S01) Applied Mathematics | K | Czech | Ostrava | 1 | Optional | study plan | ||||

2019/2020 | (N0541A170007) Computational and Applied Mathematics | (S02) Computational Methods and HPC | K | Czech | Ostrava | 1 | Optional | study plan |

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