310-3241/01 – Stochastic Methods of Modelling (S)

Gurantor departmentDepartment of Mathematics and Descriptive GeometryCredits3
Subject guarantorMgr. Marcela Rabasová, Ph.D.Subject version guarantorMgr. Marcela Rabasová, Ph.D.
Study levelundergraduate or graduateRequirementChoice-compulsory
Study languageCzech
Year of introduction2019/2020Year of cancellation
Intended for the facultiesFMT, USPIntended for study typesMaster, Follow-up Master
Instruction secured by
LoginNameTuitorTeacher giving lectures
KAH14 Mgr. Marcela Rabasová, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Credit and Examination 2+2
Part-time Credit and Examination 6+6

Subject aims expressed by acquired skills and competences

The aim of the course is to provide theoretical and practical foundation for understanding the importance of basic probability concepts and teach the student statistical thinking as a way of understanding the processes and events around us, to acquaint him with the basic methods of gathering and analyzing statistical data, and to show how to use these general procedures in other subjects of study and in practice. Graduates of this course should be able to: • understand and use the basic terms from the combinatorics and probability theory; • formulate questions that can be answered by the data and understand principles of collecting, processing and presentation of the data; • select and use appropriate statistical methods for data analysis; • propose and evaluate conclusions (inference) and make predictions using the data. The graduate of this course should be able: • understand and use basic notions in combinatorics and probability theory • formulate questions, which can be answered based on the given data, for this purpose learn the principles of collecting, processing data and presentation of relevant values and results • choose and use suitable statistical methods for data analysis • suggest and evaluate conclusions (inference) and predictions obtained from data

Teaching methods

Individual consultations
Other activities


Combinatorics and probability. Random events, operations with them, sample space. Definitions of events' probability - classical, geometrical, statistics. Conditional probability. Total probability and independent events. Random variable and its characteristics. Basic types of probability distributions of discrete random variables. Basic types of probability distributions of continuous random variables. Random vector, probability distribution, numerical characteristics. Statistical file with one factor. Grouped frequency distribution. Statistical file with two factors. Regression and correlation. Random sample, point and interval estimations of parameters. Hypothesis testing.

Compulsory literature:

Dummer R. M.: INTRODUCTION TO STATISTICAL SCIENCE. VŠB-TU Ostrava 1998; ISBN 80-7078-497-0

Recommended literature:

Dummer R. M.: INTRODUCTION TO STATISTICAL SCIENCE. VŠB-TU Ostrava 1998; ISBN 80-7078-497-0

Way of continuous check of knowledge in the course of semester

Two tests, 1 project - data analysis.



Other requirements



Subject has no prerequisities.


Subject has no co-requisities.

Subject syllabus:

1. Combinatorics 2. Introduction to probability 3. Conditional probability and independent events. Bayes' theorem. Theorem of total probability. 4. Random variable and its characteristics 5.-7. The basic distributions of discrete and continuous random variable 8. Random vector 9. Statistical file with one factor 10. Statistical file with two factors 11. Regression and correlation 12. Point and interval estimates of parameters 13. Hypothesis testing 14. Reserve

Conditions for subject completion

Full-time form (validity from: 2019/2020 Winter semester)
Task nameType of taskMax. 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  21
Mandatory attendence parzicipation: 80%

Show history

Occurrence in study plans

Academic yearProgrammeField of studySpec.ZaměřeníFormStudy language Tut. centreYearWSType of duty
2020/2021 (N0719A270002) Nanotechnology P Czech Ostrava 2 Choice-compulsory type B study plan
2019/2020 (N3942) Nanotechnology (3942T001) Nanotechnology P Czech Ostrava 1 Choice-compulsory study plan
2019/2020 (N0719A270002) Nanotechnology P Czech Ostrava 2 Choice-compulsory type B study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner