Random Phenomena

Recommended Prerequisites

Not applicable.

 

Teaching Methods

The course is composed in a way that student can simultaneously gain knowledge from proposed sheets, that

he or she gets the material in front of every course. The laboratory work is composed in a way to upgrade the

material from the theoretical course. In courses active student contribution with questions and comments is

needed.

For positive and successful execution of student obligations and connecting student in studying work the

presence in theoretical and practical course on regular basis is needed (presence at least 80% of courses), use

of extra learning material and additional preparation after working in laboratory environment and active work

on practical courses.

Oral/written exams, colloquia, seminar papers, also credit assessment of individual (verifiable) study

achievements.

The exam consists of a written part and oral questioning (50%/50%).

Laboratory work (100%).

Overall grade is from exam/laboratory work (100%/100%).

Learning Outcomes

This course intends to supply the student with the ability to:

1. to introduce the concepts of variability, description, characterization and interpretation of random data

2. to acquaint the students with the concept of probability and the basic statistical methods for the description and characterization of random data

3. to equip the students with the basic knowledge for the analysis, description, characterization and interpretation of experimental data

4. using the Matlab environment

5. the ability to analyze, characterize and interpret variable random data

6. the ability to conduct linear analysis and characterize sensor signals using the methods of technical statistics for the description, analysis, characterization, design and planning of products, technical systems and processes.

Work Placement(s)

No

Syllabus

1. Introduction: examples of random phenomena and the problem of variability in the engineering, experiments and randomness of experiment outcomes, events. 2. Probability: relations and event probabilities; random variables and probability distributions, functions of random variables; means and moments of random variables. 3. Technical statistics: important statistics, properties and probability distributions of statistics; point estimates; methods for determining estimates; interval estimates; statistical hypotheses, tests and deduction; errors of deduction; goodness-of-fit tests, tests for dependence and homogeneity; analysis of variance; function estimates: parametric and non-parametric regression. 4. Random processes: examples of random processes; moments and characteristics; stationaries and periodicity; linear transforms of random processes, autocorrelation function, spectral density, coherence function, examples of random process characterization.

Assessment Methods

Assessment
The exam consists of a written part and oral questioning (50%/50%). Laboratory work (100%). Overall grade is from exam/laboratory work (100%/100%).: 100.0%

Bibliography

[1] I. Grabec, J. Gradišek: Naključni pojavi; Fakulteta za strojništvo, 2000;

[2] E. Govekar; lecture notes; www.nakljucnipojavi.si (2007);

[3] R. Jamnik: Verjetnostni račun in statistika; Zveza organizacij za tehnično kulturo, (1986);

[4] D. C. Montgomery in G. C. Runger: Applied Statistics and Probability for Engineers, John Wiley & Sons, Inc.,

New York, 1994;

[5] J. S. Bendat, A. G. Piersol: Random Data: Analysis and measurement Procedures; Wiley-Interscience (1971);

[6] W. B. Davenport, Jr.: Probability and Random Processes: An Introduction for Applied Scientists and

Engineers, McGraw-Hill, New York, 1970;

[7] R. C. Jaffe: Random signals for engineers usnig Matlab and Mathcad; Spriger Verlag (2000).