Title:

# Statistic methods of data processing

Code:QM7
Ac.Year:ukončen 2003/2004
Sem:Winter
Language of Instruction:Czech
Completion:examination (verbal)
Type of
instruction:
Hour/semLecturesSeminar
Exercises
Laboratory
Exercises
Computer
Exercises
Other
Hours:390000
ExamsTestsExercisesLaboratoriesOther
Points:1000000
Guarantor:Zapletal Josef, doc. RNDr., CSc. (DMAT)
Faculty:Faculty of Electrical Engineering and Communication BUT
Department:Department of Mathematics FEEC BUT

Learning objectives:
To show the possibilites of statistical methods for solving of research problems in technical research on concrete examples.
Description:
Importance of statistical methods. Describing statistics. Analysis of time series. Indexes analysis. Random events and probability. Random variable and its characteristics. Random vector. The important distributions. Mathematical statistics. The testing of hypotheses. Regression analysis.
Learning outcomes and competencies:
The graduate of course would be able to use possibilities of statistical analysis for solving of concreete research problems of technical practice.
Syllabus of lectures:

1. Describing statistics. The basic sample. Statistical signs. One-dimensional statistical samples with quantitatv sign. Frequency.
2. Time series analysis. Trends. Floating means. Periodicity. Correlations.
3. Indexes analysis. Individual indexes. Summary indexes. Indexes and absolute values. Basical and string indexes.
4. Elementarz random event, operations among events. Boolean algebra of events. Classical and axiomatical definition of probability. The notion of independence of events. Bernoully sequences.
5. The random variable, the distributive function. Random vector.Simultaneous and marginal function of density and distributive function.
6. Moment's characteristics.General moments and central moments.
7. Some important distrubutions applicable on solving of problems of opereach research and important for statistical research.
8. The law of great numbers. Limit theorems.
9. The notion of random sample. The sample characteristics - statistics. Testing of hypotheses. Errors of the first and second kind. Parametrical tests.
10. Testing of one group of samples.
11. Application of the department§s software on various groups tests - without interaction, with interaction.
12. Chi square test, Kolmogorov-Smirnov test.
13. Correlation analysis. Sperman's correlation coefficient.
Progress assessment:
The form of consultations.