Many types of measurements are made routinely in research organizations, business and industry, and government and academic agencies. Typically, data are generated from experimental effort or as observational studies. From such data, management decisions are made that may have wide-reaching social, economic, and political impact. Data and decision making go hand in hand and that is why the quality of any measurement is importantfor data originate from a measurement process. This guide presents selected concepts and methods useful for describing and understanding the measurement process. This guide is not intended to be a comprehensive survey of this topic.

Any measurement result will be said to originate from a measurement process or system. The measurement process will consist of a number of input variables and general conditions that affect the final value of the measurement. The process variables, hardware and software and their properties, and the human effort required to obtain a measurement constitute the measurement process. A measurement process will have several properties that characterize the effect of the several variables and general conditions on the measurement results. It is the properties of the measurement process that are of primary interest in any such study. The term "measurement systems analysis" or MSA study is used to describe the several methods used to characterize the measurement process.

Note 1-Sample statistics discussed in this guide are as described in Practice E2586; control chart methodologies are as described in Practice E2587.