470-6403/04 – Basic Methods of Statistical Data Analysis in Practice (SMIP)

Gurantor departmentDepartment of Applied MathematicsCredits10
Subject guarantorprof. Ing. Radim Briš, CSc.Subject version guarantorprof. Ing. Radim Briš, CSc.
Study levelpostgraduateRequirementChoice-compulsory type B
YearSemesterwinter + summer
Study languageEnglish
Year of introduction2019/2020Year of cancellation
Intended for the facultiesFS, HGF, USP, FAST, FEI, FMTIntended for study typesDoctoral
Instruction secured by
LoginNameTuitorTeacher giving lectures
BRI10 prof. Ing. Radim Briš, CSc.
LIT40 Ing. Martina Litschmannová, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Examination 28+0
Part-time Examination 28+0

Subject aims expressed by acquired skills and competences

The objective of the course is to develop sufficient knowledge of statistical tools and procedures in applied engineering fields.

Teaching methods

Lectures
Project work

Summary

The course will emphasize methods of applied statistics and data analysis. Theoretical considerations will be included to the extent that knowledge of theory is necessary for a sound understanding of methods and contributes to the development of data analysis skills and the ability to interpret results of statistical analysis. The objective of the course is to develop sufficient knowledge of statistical tools and procedures, understanding of the underlying theory on which the procedures are based, and facility in the application of statistical tools to enable the student to incorporate sound statistical methodology into other areas of his or her own work.

Compulsory literature:

Briš R., Probability and Statistics for Engineers, 2011, electronics script, Project CZ.1.07/2.2.00/15.0132. Dostupné z http://homel.vsb.cz/~bri10/Teaching/Prob%20&%20Stat.pdf Hastie T., Tibshirani R., Friedman J.: The Elements of Statistical Learning, Data Mining, Inference, and Prediction. Second Edition, Springer 2008.

Recommended literature:

James L.Johnson; Probability and Statistics for Computer Science, Wiley 2003, ISBN 0-471-32672-0

Additional study materials

Way of continuous check of knowledge in the course of semester

The student will prepare a project work closely related to the topic of the dissertation, focused on the study of knowledge within this subject. Consultation on ongoing work on the project assignment. Oral exam.

E-learning

http://www.am.vsb.cz/bris/Teaching/SMIP_PhD.rar

Other requirements

There are not defined other requirements for student.

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

Lectures: - Exploratory data analysis, types of variables, summarization of distributions. Probability theory. - Random variable and probability distribution, expected value operator and moments of probability distribution, joint and conditional distributions. - Probability models for discrete and continuous random variables. - Sampling distributions of the mean, distribution of sample proportion. - Point and interval estimation, hypothesis testing, pure significance tests, p-values Two sample tests, paired difference tests. - One factor analysis of variance, ANOVA table, multiple comparisons, post hoc analysis. - Simple linear regression model. - Multiple regression models.

Conditions for subject completion

Part-time form (validity from: 2019/2020 Winter semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of pointsMax. počet pokusů
Examination Examination   3
Mandatory attendence participation:

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Conditions for subject completion and attendance at the exercises within ISP:

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Occurrence in study plans

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2022/2023 (P0613D140021) Computational Science P English Ostrava Choice-compulsory type B study plan
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2021/2022 (P0714D270002) Control of Machines and Processes P English Ostrava Choice-compulsory type B study plan
2021/2022 (P0714D270002) Control of Machines and Processes K English Ostrava Choice-compulsory type B study plan
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2020/2021 (P0732D260003) Geotechnics and Underground Engineering P English Ostrava Compulsory study plan
2020/2021 (P0732D260003) Geotechnics and Underground Engineering K English Ostrava Compulsory study plan
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2020/2021 (P0732D260005) Civil Engineering K English Ostrava Compulsory study plan
2020/2021 (P0715D270014) Applied Mechanics K English Ostrava Choice-compulsory type B study plan
2020/2021 (P0715D270014) Applied Mechanics P English Ostrava Choice-compulsory type B study plan
2020/2021 (P0719D270003) Nanotechnology P English Ostrava Choice-compulsory type B study plan
2020/2021 (P0719D270003) Nanotechnology K English Ostrava Choice-compulsory type B study plan
2020/2021 (P0715D270012) Construction of Production Machines and Equipment K English Ostrava Choice-compulsory type B study plan
2020/2021 (P0715D270012) Construction of Production Machines and Equipment P English Ostrava Choice-compulsory type B study plan
2020/2021 (P0714D270002) Control of Machines and Processes K English Ostrava Choice-compulsory type B study plan
2020/2021 (P0714D270002) Control of Machines and Processes P English Ostrava Choice-compulsory type B study plan
2020/2021 (P0719D270006) Transport and Material Handling P English Ostrava Choice-compulsory type B study plan
2020/2021 (P0719D270006) Transport and Material Handling K English Ostrava Choice-compulsory type B study plan
2019/2020 (P0732D260005) Civil Engineering P English Ostrava Compulsory study plan
2019/2020 (P0732D260005) Civil Engineering K English Ostrava Compulsory study plan
2019/2020 (P0732D260003) Geotechnics and Underground Engineering P English Ostrava Compulsory study plan
2019/2020 (P0732D260003) Geotechnics and Underground Engineering K English Ostrava Compulsory study plan
2019/2020 (P0613D140021) Computational Science P English Ostrava Choice-compulsory type B study plan
2019/2020 (P0613D140021) Computational Science K English Ostrava Choice-compulsory type B study plan

Occurrence in special blocks

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