230-0229/01 – Applied statistics (ApSt)

Gurantor departmentDepartment of MathematicsCredits2
Subject guarantorIng. Veronika Moškořová, Ph.D.Subject version guarantorIng. Veronika Moškořová, Ph.D.
Study levelundergraduate or graduateRequirementOptional
YearSemesterwinter + summer
Study languageCzech
Year of introduction2019/2020Year of cancellation
Intended for the facultiesFASTIntended for study typesFollow-up Master, Bachelor
Instruction secured by
LoginNameTuitorTeacher giving lectures
SVE0150 Ing. Veronika Moškořová, Ph.D.
PAL39 RNDr. Radomír Paláček, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Graded credit 0+3
Part-time Graded credit 0+16

Subject aims expressed by acquired skills and competences

The students should get acquainted with the main concepts of advanced statistical methods. Knowledge of the principles of work with programming language R. On completion of this course students will acquire knowledge of methods of time series analysis, their decomposition, time series forecasting, model identification methodology and spectral analysis.

Teaching methods

Individual consultations
Tutorials

Summary

Compulsory literature:

Doležalová, J.-Pavelka, L.: Pravděpodobnost a statistika. Skriptum VŠB, Ostrava 2005. ISBN 80-248-0948-6. Otipka, P.-Šmajstrla, V.: Pravděpodobnost a statistika. Skriptum VŠB-TU, Ostrava 2006. ISBN 80-248-1194-4. ( http://www.studopory.vsb.cz/studijnimaterialy/past/past.pdf ) http://mdg.vsb.cz/portal/en/Statistics1.pdf

Recommended literature:

Meloun, M. -- Militký, J. Kompendium statistického zpracování dat: metody a řešené úlohy, Praha, Academia, 2006, 80-200-1396-2 Andrew C. Harvey. Time Series Models. Harvester wheatsheaf, 1993.

Additional study materials

Way of continuous check of knowledge in the course of semester

E-learning

http://www.studopory.vsb.cz http://mdg.vsb.cz (in Czech language)

Other requirements

There are no other requirements.

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

1. Basic using of programming languuage R - principle of the work in language R, algoritmization of statistical tasks, batch processing of data. 2. Random variables and basic characteristics - Density and cumulative density functions. 3. Parameters estimation - Point estimates, Interval estimates. 4. Tests of statistical hypothesis - Basic parametric and nonparametric tests. 5. Analysis of variance (ANOVA) - one- and multifactorial ANOVA. 6. Hierarchical cluster analysis. 7. Factor analysis - idea of the method, identification of factors. 8. Introduction to time series analysis. 9. Decomposition of time series. 10. Autocorrelation analysis. 11. Spectral anlysis. 12. Box - Jenkins methodology - model identification (AR, MA, ARMA, ARIMA, SARIMA), parameters estimation, model checking. 13. Time series prediction. 14. Presentation of statistical outputs - methodology of statistical outputs presentation, mistakes in presentation of numerical and graphical outputs.

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
Graded credit Graded credit 100  51 3
Mandatory attendence participation: At least 70% attendance at the exercises. Absence, up to a maximum of 30%, must be excused and the apology must be accepted by the teacher (the teacher decides to recognize the reason for the excuse).

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Conditions for subject completion and attendance at the exercises within ISP: Mandatory participation in the course is not required. Other conditions for subject completion will respect the individual needs of the student.

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Occurrence in study plans

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2019/2020 (N0732A260005) Civil Engineering - Geotechnics and Underground Engineering P Czech Ostrava Optional study plan
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2019/2020 (N0732A260009) Civil Engineering - Building Materials and Diagnostics of Structures P Czech Ostrava Optional study plan
2019/2020 (N0732A260011) Civil Engineering - Transport Constructions P Czech Ostrava Optional study plan
2019/2020 (N0732A260011) Civil Engineering - Transport Constructions K Czech Ostrava Optional study plan
2019/2020 (N0732A260013) Civil Engineering - Building and Industry Construction P Czech Ostrava Optional study plan
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