Szkoła Doktorska - ZUT Doctoral School
Sylabus przedmiotu Estimation of measurement uncertainty:
Informacje podstawowe
| Kierunek studiów | ZUT Doctoral School | ||
|---|---|---|---|
| Forma studiów | studia stacjonarne | Poziom | |
| Stopnień naukowy absolwenta | doktor | ||
| Obszary studiów | charakterystyki PRK | ||
| Profil | |||
| Moduł | — | ||
| Przedmiot | Estimation of measurement uncertainty | ||
| Specjalność | IT, ELECTRICAL ENGINEERING AND MECHANICAL ENGINEERING BLOCK | ||
| Jednostka prowadząca | Środowiskowe Laboratorium Miernictwa | ||
| Nauczyciel odpowiedzialny | Paweł Majda <Pawel.Majda@zut.edu.pl> | ||
| Inni nauczyciele | |||
| ECTS (planowane) | 0,5 | ECTS (formy) | 0,5 |
| Forma zaliczenia | zaliczenie | Język | angielski |
| Blok obieralny | 6 | Grupa obieralna | 2 |
Wymagania wstępne
| KOD | Wymaganie wstępne |
|---|---|
| W-1 | Differential calculus, algebra |
| W-2 | Knowledge of the basics of mathematical statistics, such as: the concept of a random variable, variance and standard deviation, testing statistical hypotheses, estimating distribution parameters probabilities. |
Cele przedmiotu
| KOD | Cel modułu/przedmiotu |
|---|---|
| C-1 | Developing the ability to classify errors and their sources. |
| C-2 | Developing the ability to estimate measurement uncertainty according to the international standard "JCGM 100 - Evaluation of measurement data - Guide to the expression of uncertainty in measurement", i.e. the so-called "GUM Guide". |
Treści programowe z podziałem na formy zajęć
| KOD | Treść programowa | Godziny |
|---|---|---|
| wykłady | ||
| T-W-1 | Basic concepts of mathematical statistics (probability distribution of dispersion, correlation of random variables, central limit theorem of probability theory, etc.). Errors add up” – what does it mean and how do you understand it? Concepts: error, uncertainty, accuracy, correction, maximum error limit. Sources of measurement errors (metrological equipment, methods, impact of environmental conditions, personnel) and measures of their uncertainty. Basic concepts in the field of estimation of measurement uncertainty (standard, complex and expanded uncertainty, coverage factor, estimation using the A and B method, uncertainty budget). "Short recipe" for estimating measurement uncertainty, special cases. Rules for assessing product compliance with specifications. The law of propagation in the analysis of correlated variables. Computer simulations of measurement uncertainty estimation using the Monte Carlo method. Monte Carlo extension for multi-input and output models. Estimation of uncertainty using the effective number of degrees of freedom; Welch-Sattertwaite formula. A method for rigorously estimating measurement uncertainty. Practical exercises in estimating measurement uncertainty. | 8 |
| 8 | ||
Obciążenie pracą studenta - formy aktywności
| KOD | Forma aktywności | Godziny |
|---|---|---|
| wykłady | ||
| A-W-1 | participation in classes | 8 |
| A-W-2 | studying the subject | 4 |
| A-W-3 | participation in the final examination | 1 |
| A-W-4 | consultations | 2 |
| 15 | ||
Metody nauczania / narzędzia dydaktyczne
| KOD | Metoda nauczania / narzędzie dydaktyczne |
|---|---|
| M-1 | Informative lecture |
| M-2 | Problem lecture |
Sposoby oceny
| KOD | Sposób oceny |
|---|---|
| S-1 | Ocena podsumowująca: Written assessment |
Zamierzone efekty uczenia się - wiedza
| Zamierzone efekty uczenia się | Odniesienie do efektów kształcenia dla dyscypliny | Odniesienie do efektów zdefiniowanych dla obszaru kształcenia | Cel przedmiotu | Treści programowe | Metody nauczania | Sposób oceny |
|---|---|---|---|---|---|---|
| ISDE_4-_IEM04.2_W01 The result of education will be extended, theoretically anchored knowledge related to the represented field and scientific discipline, as well as advanced knowledge regarding conducting scientific research, methodology of scientific work, preparing publications and presenting results. The graduate will be aware of the rules for disseminating the results of scientific work, including in the context of open access. They will also have a full understanding of the fundamental dilemmas of modern civilization, especially in relation to the latest scientific achievements in the field and discipline represented. This comprehensive knowledge will also include aspects of mathematical statistics and the ability to practically apply concepts related to measurement errors, uncertainties, estimation, correlated variable analysis and Monte Carlo simulation techniques. Thanks to this, the graduate will be ready not only to immerse himself in the latest scientific achievements, but also to effectively contribute to the development of the field in the area he is considering, presenting his results in a way that is accessible and understandable to society. | ISDE_4-_W02, ISDE_4-_W03 | — | C-1, C-2 | T-W-1 | M-1 | S-1 |
Zamierzone efekty uczenia się - inne kompetencje społeczne i personalne
| Zamierzone efekty uczenia się | Odniesienie do efektów kształcenia dla dyscypliny | Odniesienie do efektów zdefiniowanych dla obszaru kształcenia | Cel przedmiotu | Treści programowe | Metody nauczania | Sposób oceny |
|---|---|---|---|---|---|---|
| ISDE_4-_IEM04.2_K01 The result of education will be the acquisition of competences enabling understanding and critical analysis of scientific achievements and one's own contribution to the development of the field and discipline. The graduate will be aware of the need for a creative approach to solving civilization challenges, both social, research and creative. They will have the ability to initiate activities in the public interest, while being an entrepreneurial thinker. They will also acquire practical skills in the practical applications of mathematical statistics, understanding key concepts for measurements, errors, uncertainties, and being able to effectively estimate and analyze measurement uncertainties according to an international standard. Thanks to the acquired skills, the graduate will be ready to effectively contribute to scientific, social and creative development, and to practically apply knowledge in practice, while achieving high standards of analysis and understanding of problems in the field and discipline represented. | ISDE_4-_K01, ISDE_4-_K02 | — | C-1, C-2 | T-W-1 | M-1, M-2 | S-1 |
Kryterium oceny - wiedza
| Efekt uczenia się | Ocena | Kryterium oceny |
|---|---|---|
| ISDE_4-_IEM04.2_W01 The result of education will be extended, theoretically anchored knowledge related to the represented field and scientific discipline, as well as advanced knowledge regarding conducting scientific research, methodology of scientific work, preparing publications and presenting results. The graduate will be aware of the rules for disseminating the results of scientific work, including in the context of open access. They will also have a full understanding of the fundamental dilemmas of modern civilization, especially in relation to the latest scientific achievements in the field and discipline represented. This comprehensive knowledge will also include aspects of mathematical statistics and the ability to practically apply concepts related to measurement errors, uncertainties, estimation, correlated variable analysis and Monte Carlo simulation techniques. Thanks to this, the graduate will be ready not only to immerse himself in the latest scientific achievements, but also to effectively contribute to the development of the field in the area he is considering, presenting his results in a way that is accessible and understandable to society. | 2,0 | |
| 3,0 | providing more than 50% correct answers in the written assessment | |
| 3,5 | ||
| 4,0 | ||
| 4,5 | ||
| 5,0 |
Kryterium oceny - inne kompetencje społeczne i personalne
| Efekt uczenia się | Ocena | Kryterium oceny |
|---|---|---|
| ISDE_4-_IEM04.2_K01 The result of education will be the acquisition of competences enabling understanding and critical analysis of scientific achievements and one's own contribution to the development of the field and discipline. The graduate will be aware of the need for a creative approach to solving civilization challenges, both social, research and creative. They will have the ability to initiate activities in the public interest, while being an entrepreneurial thinker. They will also acquire practical skills in the practical applications of mathematical statistics, understanding key concepts for measurements, errors, uncertainties, and being able to effectively estimate and analyze measurement uncertainties according to an international standard. Thanks to the acquired skills, the graduate will be ready to effectively contribute to scientific, social and creative development, and to practically apply knowledge in practice, while achieving high standards of analysis and understanding of problems in the field and discipline represented. | 2,0 | |
| 3,0 | providing more than 50% correct answers in the written assessment | |
| 3,5 | ||
| 4,0 | ||
| 4,5 | ||
| 5,0 |
Literatura podstawowa
- JCGM 100: Evaluation of measurement data − Guide to the expression of uncertainty in measurement., Geneva, 2008
- JCGM 101: Evaluation of measurement data − Supplement 1 to the “Guide to the expression of uncertainty in measurement” − Propagation of distributions using a Monte Carlo method., 2008
- JCGM 102: Evaluation of measurement data − Supplement 2 to the “Guide to the expression of uncertainty in measurement” − Extension to any number of output quantities., 2011
Literatura dodatkowa
- JCGM 103: Evaluation of measurement data – Supplement 3 to the "Guide to the expression of uncertainty in measurement" – Modelling (ISO/IEC Guide 98-3-3)
- JCGM 104: Evaluation of measurement data − An introduction to the “Guide to the expression of uncertainty in measurement” and related documents., 2009
- JCGM 105: Evaluation of measurement data – Concepts and basic principles (ISO/IEC Guide 98-2)
- JCGM 106: Evaluation of measurement data - The role of measurement uncertainty in conformity assessment., 2012
- JCGM 107 – Evaluation of measurement data – Applications of the least-squares method (ISO/IEC Guide 98-5)
- JCGM GUM-6:2020 Guide to the expression of uncertainty in measurement - Part 6: Developing and using measurement models., 2020
- PKN-ISO/IEC Guide 99. Międzynarodowy słownik metrologii. Pojęcia podstawowe i ogólne oraz terminy z nimi związane (VIM).