Limits of Detection in Chemical Analysis: Chemical Analysis: A Series of Monographs on Analytical Chemistry and Its Applications

Details methods for computing valid limits of detection

The limit of detection is among the most important concepts in chemical analysis. In simple terms, if a chemical analyte is present at, or above, the limit of detection, it has low a priori-specified probability of escaping detection. This is distinct from the formerly used decision level, i.e., the level above which there is low a priori-specified probability of obtaining a false positive from a true analytical blank. In some cases, qualitative detection of analyte is sufficient, but in many other cases, quantification is also desired or required, e.g., total arsenic concentration in a source of potable water. In this case, the concept of limit of quantitation is also relevant because meaningful quantification is not possible at the limit of detection.

Limits of Detection in Chemical Analysis details methods for computing valid, unbiased limits of detection. It correctly and clearly explains analytical detection limit theory, thereby mitigating against incorrect detection limit concepts, methodologies and results. The book focuses exclusively on how limits of detection are correctly defined and computed for ordinary univariate chemical measurement systems (CMSs). The book features:

• Clear explanations of decision level and detection limit concepts
• Profuse illustrations with many detailed examples and cogent explanations
• Extensive use of corroborating computer simulations that are freely available to readers
• A curated short-list of important references for limits of detection
• Videos, screencasts, and animations are provided at an associated website

This book is recommended for anyone wanting to learn about limits of detection. It is written at a level that makes it easily accessible to undergraduates, graduate students and researchers in both academia and industry. Readers will learn how to properly, and rather simply, compute statistically valid limits of detection and know what their limitations are.