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Understanding Analytical Error—The Use of Controls and Blind Controls
Authors: Brian K. Nunnally, John McConnell, and Bernard McGarvey

“Analysis and Control of Variation” is dedicated to revealing weaknesses in existing approaches to understanding, reducing, and controlling variation and to recommend alternatives that are not only based on sound science, but also that demonstrably work. Example situations are used to illustrate both problems and successful methodologies. The objective of the column is to combine sound science with proven practical advice.

Reader comments, questions, and suggestions are needed to help us fulfill our objective for this column. Case studies illustrating the successful reduction or control of variation submitted by readers are most welcome. Please send your comments and suggestions to column coordinator John McConnell at john@wysowl.com.au or journal coordinating editor Susan Haigney at shaigney@advanstar.com.

KEY POINTS DISCUSSED
The following is a list of key points discussed in this article:
• The use of controls and blind controls is good science and is an expectation of any world class laboratory
• Control samples should be representative material, stable for a long period of time, be homogeneous, and have sufficient supply
• Proper control charts can illuminate best practices that can ultimately improve analytical laboratory measurements
• The best estimates for analytical error are produced by blind controls.

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