Estimation of measurement uncertainty in chemical analysis
13. Additional materials and case studies
Brief summary: This section collects some additional materials, examples and case studies on specific chemical analysis techniques.
- Course introduction
- 1. The concept of measurement uncertainty (MU)
- 2. The origin of measurement uncertainty
- 3. The basic concepts and tools
- 3.1. The Normal distribution
- Self-test 3.1
- 3.2. Mean, standard deviation and standard uncertainty
- Self-test 3.2
- 3.3. A and B type uncertainty estimates
- 3.4. Standard deviation of the mean
- Self-test 3.4
- 3.5. Rectangular and triangular distribution
- Self-test 3.5
- 3.6. The Student distribution
- Self-test 3.6
- 4. The first uncertainty quantification
- 5. Principles of measurement uncertainty estimation
- 6. Random and systematic effects revisited
- 7. Precision, trueness, accuracy
- 8. Overview of measurement uncertainty estimation approaches
- 9. The ISO GUM Modeling approach
- 9.1. Step 1 – Measurand definition
- 9.2. Step 2 – Model equation
- Self-test 9.2 A
- Self-test 9.2 B
- 9.3. Step 3 – Uncertainty sources
- 9.4. Step 4 – Values of the input quantities
- 9.5. Step 5 – Standard uncertainties of the input quantities
- Self-test 9.5
- 9.6. Step 6 – Value of the output quantity
- 9.7. Step 7 – Combined standard uncertainty
- 9.8. Step 8 – Expanded uncertainty
- 9.9. Step 9 – Looking at the obtained uncertainty
- Self-test 9 A
- Self-test 9 B
- Self test 9 C
- 10. The single-lab validation approach
- 11. Comparison of the approaches
- 12. Comparing measurement results
- 13. Additional materials and case studies
- 14. Tests and Exercises
- Frequently asked questions
- What our participants say?
- Please comment!