N_STA Applied statistics

Vysoká škola technická a ekonomická v Českých Budějovicích
léto 2026
Rozsah
2/2/0. 5 kr. Ukončení: zk.
Vyučující
Robin Kunju Mol Raj, MBA (cvičící)
Garance
prof. Ing. Marek Vochozka, MBA, Ph.D., dr. h.c.
Katedra financí podniku a ekonomie – Ústav znalectví a oceňování – Rektor – Vysoká škola technická a ekonomická v Českých Budějovicích
Dodavatelské pracoviště: Katedra financí podniku a ekonomie – Ústav znalectví a oceňování – Rektor – Vysoká škola technická a ekonomická v Českých Budějovicích
Rozvrh seminárních/paralelních skupin
N_STA/P01: Čt 8:00–9:30 H209, R. Kunju Mol Raj
N_STA/S01: Pá 9:40–11:10 I301( spojená s I302), R. Kunju Mol Raj
Omezení zápisu do předmětu
Předmět je otevřen studentům libovolného oboru.
Cíle předmětu opírající se o výstupy z učení
After successful completion of the course, the student: Knows methods of applied statistics. Decides which methods and their combinations to be used. Homogenizes various types of input data to combine these with other data Extracts statistical information from the acquired data Compares the applied methods results. Interprets his/her data analysis in the light of known facts and presently existing analyses.Uses the analysis as one of the factors to valuate assets debts risks or potential profits.
Výstupy z učení
In Applied Statistics, the students will deepen their knowledge of statistics and data processing following knowledge of statistics, mathematics and data processing so that they can use the acquired knowledge in the study and practice of expert activities. The goal of the course is to present practical econometric methods of analysis of qualitative and quantitative characteristics and, perform analyses of medium-sized datasets by methods of applied statistics. The course outcome is the development of competence in the field of statistical quality control. Students shall further deepen the knowledge of statistics and data processing in connection with knowledge of statistics, mathematics. The knowledge gained can be used in the field of their expert activity.
Osnova
  • Lectures:
  • 1. Using MATLAB for statistical data processing (data sources EXCELL, web pages, text files
  • 2. Pareto analysis, choice of data, graphic output
  • 3. Pareto analysis: Estimating future cost and benefits in itemized evaluation
  • 4. Time series – continuous and discrete functions
  • 5. Trend and DC component of time series, their meaning and elimination from data
  • 6. Spectrum of time series, Fourier analysis
  • 7. Acquiring useful data from time series, filtration
  • 8. Searching for known patterns and events in noisy time series – correlation, cross-correlation
  • 9. Quality control: Shewhart charts
  • 10. Quality control: Control charts setting, x+R CONTROL CHART, unknown irregularity recognition
  • 11. The fundamentals of insurance and betting statistics
  • 12. Histogram analysis of highest potential payout
  • 13. Statistically hardly extractable data – Non-linear economic models-finding information in statistically uniform data, Poincaré section, chaotic behavior of time series.
  • Seminars:
  • Thematic content of the seminars is the same as the content of the lectures; they are focused on the separate data processing chosen by the method in MATLAB or excel software.
  • 1. Using MATLAB for statistical data processing (data sources EXCELL, web pages, text files
  • 2. Pareto analysis, choice of data, graphic output
  • 3. Pareto analysis: Estimating future cost and benefits in itemized evaluation
  • 4. Time series – continuous and discrete functions
  • 5. Trend and DC component of time series, their meaning and elimination from data
  • 6. Spectrum of time series, Fourier analysis
  • 7. Acquiring useful data from time series, filtration
  • 8. Searching for known patterns and events in noisy time series – correlation, cross-correlation
  • 9. Quality control: Shewhart charts
  • 10. Quality control: Control charts setting, x+R CONTROL CHART, unknown irregularity recognition
  • 11. The fundamentals of insurance and betting statistics
  • 12. Histogram analysis of highest potential payout
  • 13. Statistically hardly extractable data – Non-linear economic models-finding information in statistically uniform data, Poincaré section, chaotic behavior of time series.
Literatura
    povinná literatura
  • SHEWHART, W. A., 2015. Economic control of quality of manufactured product. Eastford: Martino Fine Books. ISBN 978-1614278115.
  • LUO, A. C. J., 2017. Memorized discrete systems and time-delay. 1. vyd. Basilej: Springer. ISBN 978-3-319-82661-5.
  • BLOKDYK, G., 2020. Pareto analysis: A complete guide - 2020 Edition. Brisbane: Emereo Pty Limited. ISBN 978-1867332282.
  • OSGOOD, B. G., 2019. Lectures on the Fourier transform and its applications (Pure and applied undergraduate texts). Providence: American Mathematical Society. ISBN 978-1470441913.
  • THE MATHWORKS, INC., 2017, Statistics and Machine Learning Toolbox. User's Guide.Version 11.1 (Release 2017a) [online], [ref. 2020-06-10], 9214pp. The MathWorks, Inc., Natick, MA, USA,. From: https://www.mathworks.com/help/releases/R2017a/pdf_doc/stats/s
    doporučená literatura
  • RUTHERFORD A., 2019. Systems thinking and chaos: Simple scientific analysis on how chaos and unpredictability shape our world (and how to find order in it). VDZ. ISBN 978-1951385712.
  • MONTGOMERY D. C., 2019. Introduction to statistical quality control. New York: John Wiley & Sons. ISBN 978-1-119-65711-8.
  • 50MINUTES, 2015. Pareto's principle: Expand your business with the 80/20 rule. 50Minutes.com. ISBN 978-2806269355.
  • Mandelbrot, B. B., P. H. Cootner, E. F. Fama and W. S. Morris, 2010. Fractals and Scaling in Finance, Springer-Verlag New York Inc.
  • LANGTON, C. and V. LEVIN, 2017. The intuitive guide to Fourier analysis & spectral estimation. 1. vyd. Chicago: Mount Castle Company. ISBN 978-0913063262.
Organizační formy výuky
přednáška
seminář
tutoriál
konzultace
Komplexní výukové metody
frontální výuka
skupinová výuka - kompetice
skupinová výuka - kooperace
projektová výuka
brainstorming
partnerská výuka
kritické myšlení
samostatná práce – individuální nebo individualizovaná činnost
výuka podporovaná multimediálními technologiemi
e-learning
Studijní zátěž
AktivitaPočet hodin za semestr
Prezenční formaKombinovaná forma
Final test33
Ongoing semester test21
Příprava na průběžný test2323
Příprava na seminář, cvičení, tutoriál1552
Příprava na závěrečný test3535
Účast na přednáškách26 
Účast na semináři/cvičeních/tutoriálu/exkurzi2616
Celkem:130130
Metody hodnocení a jejich poměr
test - průběžný 30 %
test - závěrečný 70 %
Podmínky testu
Overall classification of the subject: points from the final evaluation: maximum 70 points (written exam) Points from the ongoing semester evaluation: maximum 30 points test continuous (20 %) +seminar activity (10 %). Subject rating: In order to successfully complete the subject, it is necessary to achieve a total of at least 70 % of the continuous and final evaluation under the conditions set out below. In the ongoing semester evaluation, 30 points can be obtained, i.e. 30 points. 30 %. In the final evaluation, a total of 70 points can be obtained, i.e. 70 points. 70 %. The overall classification of the subject, i.e. the total classification of the subject, is not the same as points for the final evaluation (70 - 0) + points from the ongoing semester evaluation (30 - 0): A 100 – 90, B 89,99 – 84, C 83,99 – 77, D 76,99 – 73, E 72,99 – 70, FX 69,99 – 30, F 29,99 – 0. The student of the full-time form of study is obliged to contact teaching, i.e. all but lectures, meet the mandatory 70% participation. If the participation is not fulfilled, the student will be automatically classified "-".
Vyučovací jazyk
Angličtina
  • Statistika zápisu (nejnovější)
  • Permalink: https://is.vstecb.cz/predmet/vste/leto2026/N_STA