The Measurement Model and Uncertainty

Stephen Crowder, Collin Delker, Eric Forrest and Nevin Martin ()
Additional contact information
Stephen Crowder: Sandia National Laboratories
Collin Delker: Sandia National Laboratories
Eric Forrest: Sandia National Laboratories
Nevin Martin: Sandia National Laboratories

Chapter Chapter 6 in Introduction to Statistics in Metrology, 2020, pp 103-129 from Springer

Abstract: Abstract This chapter introduces the basic terms and models used to quantify the uncertainty of both direct and indirect measurements. Basic definitions such as Type A and Type B evaluation of uncertainty are introduced, and the GUM approach to the propagation of uncertainties is explained. Case studies are used to illustrate the approaches to uncertainty analyses for both types of measurements.

Date: 2020
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-53329-8_6

Ordering information: This item can be ordered from
http://www.springer.com/9783030533298

DOI: 10.1007/978-3-030-53329-8_6

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().