310-3145/01 – Statistics for engineers (StatEn)

Gurantor departmentDepartment of Mathematics and Descriptive GeometryCredits4
Subject guarantorIng. Petra Schreiberová, Ph.D.Subject version guarantorIng. Petra Schreiberová, Ph.D.
Study levelundergraduate or graduateRequirementCompulsory
Year1Semesterwinter
Study languageCzech
Year of introduction2021/2022Year of cancellation
Intended for the facultiesFSIntended for study typesFollow-up Master
Instruction secured by
LoginNameTuitorTeacher giving lectures
SKN002 Ing. Petra Schreiberová, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Credit and Examination 2+2

Subject aims expressed by acquired skills and competences

The aim is to understand of statistical methods for data analysis. Absolvent will be able to interpret results of statistical methods in a selected statistical software.

Teaching methods

Lectures
Tutorials

Summary

Předmět je zaměřen na vysvětlení pojmů a technik pro statistickou analýzu dat. Studenti získají znalosti a dovednosti nezbytné pro použití a vyhodnocování statistických technik za použití statistického software. Po absolvování předmětu by studenti měli být schopni zřetelně formulovat řešený problém, diskutovat oprávněnost použitých postupů a s ohledem na charakter oboru vyvozovat odpovídající závěry a interpretace.

Compulsory literature:

CRAWLEY, Michael J. Statistics: an introduction using R. Chichester, West Sussex, England: J. Wiley, 2005. ISBN 978-0470022986. BOHÁČ, Zdeněk: Numerical Methods and Statistics, Ostrava: VŠB - Technická univerzita Ostrava, 2005. ISBN 80-248-0803-X

Recommended literature:

ŠKŇOUŘILOVÁ,Petra a Radim BRIŠ. Statistics I. Ostrava: VŠB - Technická univerzita Ostrava, 2007. Dostupné z: http://mdg.vsb.cz/portal/en/Statistics1.pdf

Way of continuous check of knowledge in the course of semester

Zápočet - max. 20 bodů, minimum je 5 bodů - zpracování domácích programů Zkouška - kombinovaná

E-learning

Other requirements

There are no more requirements.

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

1. Software R 2. Random variable 3. Descriptive statistics 4. Graphical analysis 5. Inductive statistics - point and interval estimation 6. Statistical hypothesis testing parametric 7. Statistical hypothesis testing neparametric 8. ANOVA 9. Contingency table 10. Linear regression 11. Multiple regression 12. Time series analysis 13. Decomposing Time Series

Conditions for subject completion

Full-time form (validity from: 2020/2021 Winter semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of pointsMax. počet pokusů
Credit and Examination Credit and Examination 100 (100) 51
        Credit Credit 20  5
        Examination Examination 80  30 3
Mandatory attendence participation: 80 %

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Conditions for subject completion and attendance at the exercises within ISP: In order to complete the credit, students pass the credit test. On the basis of a successfully completed credit, they can take an exam.

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Occurrence in study plans

Academic yearProgrammeField of studySpec.ZaměřeníFormStudy language Tut. centreYearWSType of duty
2023/2024 (N0713P070001) Ecologization of Energetics Processes P Czech Ostrava 1 Compulsory study plan
2022/2023 (N0713P070001) Ecologization of Energetics Processes P Czech Ostrava 1 Compulsory study plan
2021/2022 (N0713P070001) Ecologization of Energetics Processes P Czech Ostrava 1 Compulsory study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner

Assessment of instruction



2021/2022 Winter