Brian Brookman
= Brian Brookman
{c}
\b[Brian Brookman] works on analytical measurement quality and <proficiency testing>. His official 2026 Eurachem workshop biography describes him as an independent consultant and former Chief Scientific Officer of LGC's global proficiency-testing business. It records work on training, development of testing schemes and accreditation.<Brian Brookman biography at Eurachem Alicante 2026>[Speaker biography]{ref}
\Image[https://eurachem-ptalicante2026.org/wp-content/uploads/2025/03/Brian-Brookman.jpg]
{title=Brian Brookman, portrait supplied on the named Eurachem workshop speaker page}
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With <Ian Mann (metrology)>, Brookman co-edited the 2021 third edition of <Selection, Use and Interpretation of Proficiency Testing (PT) Schemes by Brian Brookman and Ian Mann>. The editorial page lists him as chair of its working group. The guide explains how laboratories select comparisons, interpret performance and investigate questionable results.<Selection, Use and Interpretation of Proficiency Testing (PT) Schemes by Brian Brookman and Ian Mann>[Editorial page; sections 5–8]{ref}
An original statistical example shows one reason scheme design matters. Four reported results $100,100,100,140$ have <sample mean>110 and <sample standard deviation>20. Assessing the value140 against that mean and spread gives $(140-110)/20=1.5$. If an independently justified assigned value is100 and the required assessment spread is5, the same reported value gives a <proficiency-test z-score> of8. The participant values have not changed; the reference and criterion have.
This small invented dataset is not a prescription to estimate a real scheme from four participants. It illustrates how an extreme result can affect a participant-derived consensus and spread. The guide discusses assigned values, <standard deviation for proficiency assessment> and statistical evaluation as distinct design choices. A laboratory should understand those choices before interpreting a score as a simple accuracy ranking.<Selection, Use and Interpretation of Proficiency Testing (PT) Schemes by Brian Brookman and Ian Mann>[Sections 7.2 and 8.2.3; Annex D, statistical aspects]{ref}
The scientific role of this work is to connect <measurement accuracy>, <measurement uncertainty> and externally defined performance criteria. A comparison can reveal a problem, but determining its cause still requires examination of the method, materials, <measurement calibration> and data handling.