Part I. Principles: 1. Introduction
2. Foundational ideas in measurement
3. Components of error or uncertainty
4. Foundational ideas in probability and statistics
5. The randomization of systematic errors
6. Beyond the standard confidence interval
Part II. Evaluation of Uncertainty: 7. Final preparation
8. Evaluation using the linear approximation
9. Evaluation without the linear approximations
10. Uncertainty information fit for purpose
Part III. Related Topics: 11. Measurement of vectors and functions
12. Why take part in a measurement comparison?
13. Other philosophies
14. An assessment of objective Bayesian methods
15. A guide to the expression of uncertainty in measurement
16. Measurement near a limit – an insoluble problem?