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

Gurantor department	Department of Mathematics and Descriptive Geometry	Credits	4
Subject guarantor	Ing. Petra Schreiberová, Ph.D.	Subject version guarantor	Ing. Petra Schreiberová, Ph.D.
Study level	undergraduate or graduate	Requirement	Compulsory
Year	1	Semester	winter
		Study language	Czech
Year of introduction	2021/2022	Year of cancellation
Intended for the faculties	FS	Intended for study types	Follow-up Master

Instruction secured by
Login	Name	Tuitor	Teacher giving lectures
SKN002	Ing. Petra Schreiberová, Ph.D.

Extent of instruction for forms of study
Form of study	Way 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

Additional study materials

Study supports in the EduDocs system

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. Linear regression 10. Time series analysis 11. Decomposing Time Series

Conditions for subject completion

Full-time form (validity from: 2020/2021 Winter semester)

Task name	Type of task	Max. number of points (act. for subtasks)	Min. number of points	Max. počet pokusů
Credit and Examination	Credit and Examination	100 (100)	51
Credit	Credit	20	5
Examination	Examination	80	30	3

Mandatory attendence participation: 80 %

Show history

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.

Show history

Occurrence in study plans

Academic year	Programme	Form	Study language	Tut. centre	Year	Type of duty
2024/2025	(N0713P070001) Ecologization of Energetics Processes	P	Czech	Ostrava	1	Compulsory	study plan
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 name	Academic year	Form of study	Study language	Year	W	S	Type of block	Block owner

Assessment of instruction

2023/2024 Winter

2021/2022 Winter