title: Measurement uncertainty in microbiology.
abstract: Testing laboratories wishing to comply with the requirements of ISO/IEC 17025:1999 need to estimate uncertainty of measurement for their quantitative methods. Many microbiological laboratories have had procedures available for monitoring variability in duplicate results generated by laboratory analysts for some time. These procedures, however, do not necessarily include all possible contributions to uncertainty in the calculations. Procedures for estimating microbiological method uncertainty, based on the Poisson distribution, have been published but, at times, the procedures can either underestimate uncertainty or require laboratories to undertake considerable experimental studies and more complex statistical calculations. This paper proposes procedures for estimating uncertainty of measurement in microbiology, whereby routine laboratory quality control data can be analyzed with simple statistical equations. The approaches used in these procedures are also applied to published data and examples, demonstrating that essentially equivalent results can be obtained with these procedures.
authors: Lynne I. Forster Training & Consulting Services, PO Box 15847, New Lynn, Auckland, New Zealand. lforster@clear.net.nz
authors: Lynne I
authors: LI
authors: Forster
mesh_terms: D015169:Colony Count, Microbial; D016001:Confidence Intervals; D004755:Enterobacteriaceae / Q000302:isolation & purification; D007753:Laboratories / Q000706:statistics & numerical data*; D008433:Mathematics; D008828:Microbiological Techniques / Q000706:statistics & numerical data*; D016012:Poisson Distribution; D011786:Quality Control; D035501:Uncertainty; D014871:Water Microbiology / Q000592:standards