VŠTE:NZ_STA Applied statistics - Informace o předmětu

NZ_STA Applied statistics

Rozsah

2/2/0. 5 kr. Ukončení: zk.

Vyučující

RNDr. Ivo Opršal, Ph.D. (cvičící)

Garance

RNDr. Ivo Opršal, Ph.D.
Katedra informatiky a přírodních věd – Ústav technicko-technologický – Rektor – Vysoká škola technická a ekonomická v Českých Budějovicích
Dodavatelské pracoviště: Katedra informatiky a přírodních věd – Ústav technicko-technologický – Rektor – Vysoká škola technická a ekonomická v Českých Budějovicích

Rozvrh seminárních/paralelních skupin

NZ_STA/P01: Pá 8:00–9:30 D315, I. Opršal
NZ_STA/S01: Pá 9:40–11:10 D315, I. Opršal

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.
• 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
• OSGOOD, B. G., 2019. Lectures on the Fourier transform and its applications (Pure and applied undergraduate texts). Providence: American Mathematical Society. ISBN 978-1470441913.
• BLOKDYK, G., 2020. Pareto analysis: A complete guide - 2020 Edition. Brisbane: Emereo Pty Limited. ISBN 978-1867332282.

doporučená literatura
• MONTGOMERY D. C., 2019. Introduction to statistical quality control. New York: John Wiley & Sons. ISBN 978-1-119-65711-8.
• LANGTON, C. and V. LEVIN, 2017. The intuitive guide to Fourier analysis & spectral estimation. 1. vyd. Chicago: Mount Castle Company. ISBN 978-0913063262.
• 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.
• 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.

Organizační formy výuky

bloková výuka - tutoriál

Komplexní výukové metody

frontální výuka
skupinová výuka - kompetice
skupinová výuka - kooperace
brainstorming
kritické myšlení
samostatná práce – individuální nebo individualizovaná činnost
výuka podporovaná multimediálními technologiemi
e-learning

Studijní zátěž

Aktivita	Počet hodin za semestr
	Prezenční forma	Kombinovaná forma
Final test		3
Ongoing semester test		1
Příprava na průběžný test		23
Příprava na seminář, cvičení, tutoriál		52
Příprava na závěrečný test		35
Účast na semináři/cvičeních/tutoriálu/exkurzi		16
Celkem:	0	130

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 "F".

Vyučovací jazyk

Angličtina

• Statistika zápisu (nejnovější)
  
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