|Course title||Statistical Evaluation of Experimental Data|
|Organizational form of instruction||Lecture + Lesson|
|Level of course||Bachelor|
|Year of study||not specified|
|Frequency of the course||In each academic year, in the winter semester.|
|Number of ECTS credits||5|
|Language of instruction||Czech|
|Status of course||Compulsory, Compulsory-optional|
|Form of instruction||Face-to-face|
|Work placements||This is not an internship|
|Recommended optional programme components||None|
Content of lectures: 1. Definition of probability - classical, statistical, axiomatic 2. Conditional probability and Bayer pattern 3. Random variable, distribution and the frequency function 4. The probability density, statistical moments, the central limit theorem 5. Binomial, Poisson, uniform, Gaussian probability distribution 6. Correlation function, covariance, power spectral density, Wiener- Khinchin theorem 7. Composite statistical systems 8. Random vector, its description and the description of its distribution, joint distribution function 9. Statistics - statistical files, basic concepts 10. Statistical ensemble with one argument - the basic characteristics 11. Processing of a large statistical ensemble 12. Correlation and regression - the least squares method, linear and nonlinear regression 13. Parameters estimation of the ensemble - point and interval estimates of the parameters of the basic ensemble. 14. Testing of statistical hypotheses - hypotheses about the variance, mean value. Goodness of fit test and the test of extreme values. Content of practicals: Statistical methods will be used on examples of various physical problems (Brownian motion, power spectral density, temperature fluctuations, electronic noise, etc.)
|Learning activities and teaching methods|
Monologic (reading, lecture, briefing), Work with text (with textbook, with book), E-learning, Individual preparation for exam, Group work
To acquaint students with basic concepts of probability theory and mathematical statistics. Probability definitions, continuous and discrete random variables, discrete and continuous probability distributions and distribution functions will be discussed. Students will also learn the law of large numbers or the central limit theorem. The course will also focus on describing estimation functions and their properties, displaying random data or constructing confidence intervals. The topics discussed will be practiced on interesting examples.
The graduate gains an overview of the basics of probability theory and mathematical statistics. Based on this knowledge he/she will be able to solve problems in the field of probability and statistics. When working with software tools, they will have an idea of the statistical analyzes provided by these modern software tools. They will apply their knowledge in practice, eg when analyzing the results of experiments.
Knowledge of the basics of mathematical analysis, as taught in the first two semesters at the University.
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UMB/564 and UMB/565
|Assessment methods and criteria|
Active mastering of the curriculum in the range of lectures given by the thematic plan of the course. Credit: attendance at seminars and active participation in calculating examples. Examination: demonstration of knowledge at the minimum of 75%. During the oral exam, the student will be asked one question from the theory of probability and one question from mathematical statistics.
|Study plans that include the course|
|Faculty||Study plan (Version)||Category of Branch/Specialization||Recommended year of study||Recommended semester|
|Faculty: Faculty of Science||Study plan (Version): Physics for future teachers (1)||Category: Physics courses||-||Recommended year of study:-, Recommended semester: Winter|
|Faculty: Faculty of Science||Study plan (Version): Measuring and Computer Technology (1)||Category: Electrical engineering, telecommunication and IT||2||Recommended year of study:2, Recommended semester: Winter|
|Faculty: Faculty of Science||Study plan (Version): Biophysics (1)||Category: Physics courses||2||Recommended year of study:2, Recommended semester: Winter|
|Faculty: Faculty of Science||Study plan (Version): Physics (1)||Category: Physics courses||2||Recommended year of study:2, Recommended semester: Winter|
|Faculty: Faculty of Science||Study plan (Version): Mechatronics (1)||Category: Special and interdisciplinary fields||2||Recommended year of study:2, Recommended semester: Winter|