Cookies

Like most websites The Analytical Scientist uses cookies. In order to deliver a personalized, responsive service and to improve the site, we remember and store information about how you use it. Learn more.
Techniques & Tools Data Analysis

Why We Need the Theory of Sampling

The purpose of sampling is to extract a representative amount of material from a ‘lot’ – the ‘sampling target’. It is clear that sampling must and can only be optimized before analysis. In a recent paper, we show how non-representative sampling processes will always result in an invalid aliquot for measurement uncertainty (MU) characterization (1).

A specific sampling process can either be representative – or not. If sampling is not representative, we have only undefined, mass-reduced lumps of material without provenance (called ‘specimens’ in the theory of sampling) that are not actually worth analyzing. Only representative aliquots reduce the MU of the full sampling-and-analysis process to its desired minimum; and it is only such MU estimates that are valid. Sampling ‘correctness’ (which we define later) and representativity are essential elements of the sampling process.

Read the full article now

Log in or register to read this article in full and gain access to The Analytical Scientist’s entire content archive. It’s FREE and always will be!

Login if you already created an account

Or register now - it’s free and always will be!

You will benefit from:

  • Unlimited access to ALL articles
  • News, interviews & opinions from leading industry experts
  • Receive print (and PDF) copies of The Analytical Scientist magazine
Register

Or Login as a Guest or via Social Media

About the Authors

Author Kim Esbensen

Kim H. Esbensen

Kim Esbensen is a research professor in Geoscience Data Analysis and Sampling at GEUS (National Geological Surveys of Denmark and Greenland), chemometrics professor with the ACABS research group, Aalborg University, Denmark, and external professor of process analytical technologies (PAT) at the Telemark Institute of Technology, Norway. Somehow, Kim also finds time to be a member of seven international societies and chairman of the DS-Forum 205 taskforce, responsible for writing the world’s first horizontal (matrix- independent) sampling standard. “I like to get involved...”he says, “And I have devoted all my research to the theme of representative sampling of heterogeneous systems and PAT.” 


author claas wagner

Claas Wagner

Originally trained as an economist, Claas Wagner realized that his real interests were with environmental and energy related topics. Sustainable resource management, emission reduction procedures and energy efficiency issues share common ground: decisions need to be based on valid data. This led to Claas’ PhD on representative sampling and data analysis for quality monitoring in large-scale combustion plants. Currently, Claas combines his fields of interest as a consultant for various industries, providing quality assurance approaches. Throughout all of his work reigns representative sampling.

Newsletter

Send me the latest from The Analytical Scientist.

Sign up now

Related Articles

Business & Education Technology

A Philadelphia Story

| Joanna Cummings

Fields & Applications Proteomics

Landmark Literature 2018: Part II

| Sergio C. Nanita, Mikhail Savitski, Ken Broeckhoven, Jean-Francois Masson, Anneli Kruve, Juris Meija, Cecilia Cagliero, Hiroshi Tsugawa

Fields & Applications Technology

The Lie of the Land

| Charlotte Barker

Register to The Analytical Scientist

Register to access our FREE online portfolio, request the magazine in print and manage your preferences.

You will benefit from:

  • Unlimited access to ALL articles
  • News, interviews & opinions from leading industry experts
  • Receive print (and PDF) copies of The Analytical Scientist magazine

Register