455-0056/01 – Statistical processing of measurements (SZM)
Gurantor department | Department of Measurement and Control | Credits | 4 |
Subject guarantor | prof. Ing. Marek Penhaker, Ph.D. | Subject version guarantor | prof. Ing. Marek Penhaker, Ph.D. |
Study level | undergraduate or graduate | Requirement | Choice-compulsory |
Year | | Semester | summer |
| | Study language | Czech |
Year of introduction | 1992/1993 | Year of cancellation | 2002/2003 |
Intended for the faculties | FEI | Intended for study types | Master |
Subject aims expressed by acquired skills and competences
The goal of this subject is to obtain knowledge in statistical search analysis of one-dimensional measured data.
The Graduate will obtain theoretical and practical knowledge of Statistical processing of measurements theory
The Graduate will obtain theoretical and practical knowledge of Statistical processing of measurements theory.
Teaching methods
Summary
The goal of this subject is to obtain knowledge in statistical search analysis of one-dimensional measured data. The Graduate will obtain theoretical and practical knowledge of Statistical processing of measurements theory.
This subject presents engineering methods of statistical analysis. The subject content includes a wide range of common statistical tasks, from random number generation, to curve fitting, to design of experiments and statistical process control. For the practice statistical reckoning MATLAB Statistics Toolbox is used. This toolbox thus supplies engineers, scientists, researchers, financial analysts, and statisticians with the statistical software they need to assess and understand their data.
Compulsory literature:
Pokorný, M. - Kozub, R.: Statistické zpracování měřených dat I, Ostrava, skripta VŠB - TU Ostrava, 1998
Hátle, J. - Likeš, J.: Základy počtu pravděpodobnosti a matematické statistiky. Praha, SNTL 1974.
Meloun, M. - Militký, J.: Chemometrie - zpracování experimentálních dat na IBM-PC. Praha, SNTL 1990.
Likeš,J.: Matematická statistika, SNTL Praha 1988
Recommended literature:
J. Zapletal:Základy počtu pravděpodobnosti a matematické statistiky,PC-DIR , Brno 1995
J. Díblík , A. Haluzíková , J. Baštinec :Numerická matematika a matematická statistika,SNTL , Praha 1987
A. Haluzíková , V. Kudláček , B. Zástěra:Numerické metody a matematická statistika,VUT Brno 1979
Penhaker,M: Statistical processing of measurements,Sylabus on WWW pages of department,2002
Way of continuous check of knowledge in the course of semester
Verification of study:
2 x tests and semestral work
Conditions for credit:
semestral work - maximum 10 points, 2x tests each maximum 20 points. On the whole maximum 50 points and minimum - 25 points.
E-learning
Other requirements
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
Lectures:
Diversifikation of measurement deficiency. Sensitivity response of instrumentation. Models of measurement and error estimation.
error results in instrumentation measurements. Method of Taylor expansion,
Describing statistics. The basic sample. Statistical signs. One-dimensional statistical samples with quantitative sign. Frequency.
Random Variables of one and two variables, their distributive and density functions.
Statistical graphs identification of data unique. Dispersed diagram, box diagram, notch diagram.
Construction and identification of distribution selection. Main type of distribution. Core estimation of frequency function. Histogram.
Transformation of data. Inverse transform.
Verification of data presumption. Minimal size of selection, normality, homogeneity of selection. Conclusion of investigation progress in one dimensional analysis.
Statistics of one dimensional data. Spot estimation of position parameters, dispersions and form.
Robust estimation of positions parameters and dispersions.
Testing of statistical hypothesis. Tests of parametric hypothesis of one and two files. Conclusion of one dimensional selection.
Difussion analysis introduction (ANOVA)
One-factor ANOVA
Two-factor ANOVA
Computer labs:
Abstract of available program systems for analysis and statistical processing on PC. Main operation within data, interactive flow of calculations.
Example of error result processing. Introduction into MATLAB and Statistic ToolBox
Example of data graphical analysis.
Example of data graphical analysis.
Determination of histogram, frequency function estimation. Different type of distribution.
Examples elaboration for transformation data, estimation of selection.
Data independence test, minimum range of selection, normality, homogeneity. Submission of semestral work.
Examples of describing statistics. The basic sample. Statistical signs. One-dimensional statistical samples with quantitative sign. Frequency.
One-dimensional statistics. Examples for classical parameters estimation.
One-dimensional statistics. Robust estimation of positions parameters and dispersions.
One-dimensional statistics. Summary examples.
Discussion about semestral work
Examples for processing data by the method dispersion analysis. Gift-over semestral work.
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction
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