All who have introductory level knowledge of analytical chemistry
The students who have successfully passed the course will be issued a certificate of completion by the University of Tartu.
A digital certificate of completion is free of charge. Please read the technical requirements for downloading and opening the digitally verified document here.
Introductory level knowledge of analytical chemistry is required. More advanced knowledge of analytical chemistry and introductory knowledge of mathematical statistics is an advantage.
This is an introductory course on estimation of measurement uncertainty, specifically related to chemical analysis (analytical chemistry). The course gives the main concepts and mathematical apparatus of measurement uncertainty estimation and introduces two principal approaches to measurement uncertainty estimation – the ISO GUM modeling approach (the “bottom-up” or modeling approach) and the single-lab validation approach as implemented by Nordtest (the “top-down” or Nordtest approach). The course contains lectures, practical exercises and numerous tests for self-testing.
In spite of being introductory, the course intends to offer sufficient knowledge and skills for carrying out uncertainty estimation for most of the common chemical analyses in routine laboratory environment. The techniques for which there are examples or exercises include acid-base titration, Kjeldahl nitrogen determination, UV-Vis spectrophotometry, atomic absorption spectroscopy and liquid chromatography mass spectrometry (LC-MS). It is important to stress, however, that for successful measurement uncertainty estimation experience (both in analytical chemistry as such and also in uncertainty estimation) is crucial and this can be acquired only through practice.
The materials of this course can also be useful for people who do not intend to follow the full course but only want to find answers to some specific questions.
Successfully completing the course means that all graded tests are taken successfully. At the end of each study week there is a graded test (Test 1 Quiz, Test 2 Quiz, ...). All 6 tests have to be taken and with each test the score has to be equal to or higher than the threshold (the threshold is indicated with each test). Each test can be taken a number of times (the number of allowed attempts is indicated with each test). The highest obtained score will count.
The final score will be formed by weighted summation of scores of all tests.
The student who has successfully passed the course knows:
- the main concepts related to measurement results and measurement uncertainty, including their application to chemical analysis;
- the main mathematical concepts and tools in uncertainty estimation;
- the main measurement uncertainty sources in chemical analysis;
- the main approaches for measurement uncertainty estimation.
The student who has successfully passed the course is able to:
- decide what data are needed for uncertainty estimation, understand the meaning of the available data and decide whether the available data are sufficient;
- select the uncertainty estimation approach suitable for the available data;
- quantify the uncertainty contributions of the relevant uncertainty sources using the available data;
- carry out estimation of uncertainty using the main approaches of uncertainty estimation.
This course is part of the Applied Measurement Science (http://www.ut.ee/ams/) master’s programme, which offers “full package” of education in Analytical chemistry, physical measurements and testing, metrology in chemistry, as well as economic and legal aspects of measurements.
You are all welcome to apply for a place in the AMS programme!
- The feedback of the participants was very positive (some examples can be seen on the course website) and we are glad that evidently we were able to offer something that is really needed by people who do chemical analysis in their everyday work, such as many of our participants.
- This possibility for everyone to work at their own pace has been specifically outlined in several participant feedbacks as a strong point.