The contents of this book provide beyond doubt the most important topics an applied mathematician, physicist, engineer, or anyone working in any quantitative discipline can be exposed to. It is also fair to bet that anyone working in these disciplines has encountered these topics early on in their professional careers, as they are usually the first ones presented to incoming freshman in beginning engineering and physics laboratories. When performing elementary laboratory experiments, beginning students find out right away that their results do not match the perfections of textbook equations. Experimental apparatus is never infinitely precise and frequently mistakes are made in experimental work repeatedly and unknowingly by the experimentalist, engineer, or scientist. Errors and uncertainties accompany any experiment that is conducted in the real world, and how to deal with them is the subject of error analysis, which is now called "uncertainty quantification" in more modern parlance. This subject is vast and in many ways very controversial, and modern technological developments have instigated a lot of research in this area.This excellent book gives an elementary overview of the techniques of error analysis that touches on topics such as uncertainty, propagation of errors, and systematic error. Readers will only require a rudimentary background in mathematics and statistics in order to read and study it. Numerous "quick" practice exercises are embedded in the main text, giving readers immediate challenges to their understanding as they read the text. Problem sets accompany each chapter, and they reflect the kinds of problems that one would encounter in real practice.Error analysis (uncertainty quantification) is certainly the most important activity behind any kind of scientific research and mathematical and simulation modeling. The comparison of results of models to empirical data cannot be done meaningfully without the tools outlined in this book and others. It is therefore very disheartening to find, as the reviewer has on numerous occasions, that any cognizance of errors or uncertainties in modeling and experimental efforts is completely absent. In some contexts, such as research on medical devices and national defense, this omission can be extremely dangerous and actually cause loss of life. The origins of why the practice of error analysis has been forgotten or omitted is unknown, but those individuals who do would gain considerably by a careful study of this book. It would be the most important refresher course that they could take in their professional careers.