Reliable and metrologically comparable results of quantitative analytical methods are essential to assure that decisions taken on their basis have meaning and context. Problems with combining measurement results, calculating their uncertainties and establishing metrological traceability can prove complicated and ambiguous for measurement scientists. Combining and Reporting Analytical Results discusses in detail the problems faced by scientists, and presents a variety of approaches across biological, chemical and environmental sciences to resolving these types of issues. Topics include: validated methods of analysis; application of internal quality control procedures; participation in proficiency testing schemes; metrological traceability of measurement results and associated uncertainties, as well as some quality system issues and formal accreditation. Written by leading experts, and with worked examples and illustrations throughout, this invaluable reference source is ideal for analysts from various scientific fields.

The environment for obtaining information and providing statistical data for policy makers and the public has changed significantly in the past decade, raising questions about the fundamental survey paradigm that underlies federal statistics. New data sources provide opportunities to develop a new paradigm that can improve timeliness, geographic or subpopulation detail, and statistical efficiency. It also has the potential to reduce the costs of producing federal statistics. The panel's first report described federal statistical agencies' current paradigm, which relies heavily on sample surveys for producing national statistics, and challenges agencies are facing; the legal frameworks and mechanisms for protecting the privacy and confidentiality of statistical data and for providing researchers access to data, and challenges to those frameworks and mechanisms; and statistical agencies access to alternative sources of data. The panel recommended a new approach for federal statistical programs that would combine diverse data sources from government and private sector sources and the creation of a new entity that would provide the foundational elements needed for this new approach, including legal authority to access data and protect privacy. This second of the panel's two reports builds on the analysis, conclusions, and recommendations in the first one. This report assesses alternative methods for implementing a new approach that would combine diverse data sources from government and private sector sources, including describing statistical models for combining data from multiple sources; examining statistical and computer science approaches that foster privacy protections; evaluating frameworks for assessing the quality and utility of alternative data sources; and various models for implementing the recommended new entity. Together, the two reports offer ideas and recommendations to help federal statistical agencies examine and evaluate data from alternative sources and then combine them as appropriate to provide the country with more timely, actionable, and useful information for policy makers, businesses, and individuals.

A Practical Tool for Learning New Methods Quality assurance and measurement uncertainty in analytical laboratories has become increasingly important. To meet increased scrutiny and keep up with new methods, practitioners very often have to rely on self-study. A practical textbook for students and a self-study tool for analytical laboratory employees, Quality Assurance and Quality Control in the Analytical Chemical Laboratory: A Practical Approach defines the tools used in QA/QC, especially the application of statistical tools during analytical data treatment. Unified Coverage of QA in Analytical Chemistry Clearly written and logically organized, this book delineates the concepts of practical QA/QC, taking a generic approach that can be applied to any field of analysis. Using an approach grounded in hands-on experience, the book begins with the theory behind quality control systems and then moves on to discuss examples of tools such as validation parameter measurements, the use of statistical tests, counting the margin of error, and estimating uncertainty. The authors draw on their experience in uncertainty estimation, traceability, reference materials, statistics, proficiency tests, and method validation to provide practical guidance on each step of the process. Extended Coverage of QC/QA in Analytical and Testing Laboratories Presenting guidance on all aspects of QA and measurement results, the book covers QC/QA in a more complex and extended manner than other books on this topic. This range of coverage supplies an integrated view on measures like the use of reference materials and method validation. With worked-out examples and Excel spreadsheets that users can use to try the concepts themselves, the book provides not only know-what but know-how.

It is now becoming recognized in the measurement community that it is as important to communicate the uncertainty related to a specific measurement as it is to report the measurement itself. Without knowing the uncertainty, it is impossible for the users of the result to know what confidence can be placed in it; it is also impossible to assess the comparability of different measurements of the same parameter. This volume collects 20 outstanding papers on the topic, mostly published from 1999-2002 in the journal "Accreditation and Quality Assurance." They provide the rationale for why it is important to evaluate and report the uncertainty of a result in a consistent manner. They also describe the concept of uncertainty, the methodology for evaluating uncertainty, and the advantages of using suitable reference materials. Finally, the benefits to both the analytical laboratory and the user of the results are considered.