ISO 11843-6:2025
Capability of detection — Part 6: Methodology for the determination of the critical value and the minimum detectable value in Poisson distributed measurements by normal approximations
Capability of detection — Part 6: Methodology for the determination of the critical value and the minimum detectable value in Poisson distributed measurements by normal approximations
- Статус документа:
- Действующий
- Формат:
- Электронный (PDF)
- Количество страниц:
- 21
- Дата публикации:
- 23 октября 2025 г.
- Издание:
- ISO IS 11843 edition 3 version 1
- ICS:
- 03.120.30
This document presents methods for determining the critical value of the response variable and the minimum detectable value in Poisson distribution measurements. It is applicable when variations in both the background noise and the signal are describable by the Poisson distribution. The conventional approximation is used to approximate the Poisson distribution by the normal distribution consistent with ISO 11843-3 and ISO 11843-4. The accuracy of the normal approximation as compared to the exact Poisson distribution is discussed in Annex B.
Abstract
Overview
ISO 11843-6:2025 - Capability of detection, Part 6 - defines a statistical methodology for determining the critical value and the minimum detectable value (MDV) when both signal and background follow a Poisson distribution. The standard uses the conventional normal approximation to the Poisson law (consistent with ISO 11843-3 and ISO 11843-4) to compute decision thresholds, and it discusses the accuracy of that approximation (Annex B).
Key topics and requirements
- Scope and assumptions
- Applicable when variations in background and signal are describable by the Poisson distribution.
- Uses the normal approximation to derive variances, critical values and MDVs.
- Decision criteria
- Defines the critical value (yC) for the response variable to control the probability of false detection (α, error of the first kind).
- Defines the MDV (gx) tied to the probability of failing to detect a true signal (β, error of the second kind).
- Computation and reporting
- Provides formulae for computing yC using standard-normal quantiles and observed means/variances (Clause 6).
- Includes guidance on estimating mean and variance under normal approximation (Annex A) and examples (Annex D).
- Specifies reporting requirements for capability assessments and applications (Clauses 7 and 8).
- Practical measurement constraints
- Both signal and background must be raw, unprocessed counts.
- Prefer longer single measurements over many short ones (improves normal approximation).
- Repeat measurements are required to estimate means reliably.
- Detector must operate in its linear counting range; number of channels and FWHM must match between blank and sample (Annex C).
Applications and users
- Targeted at laboratories and instrument operators using pulse-counting detectors and spectroscopy techniques where counts follow Poisson statistics:
- X-ray fluorescence (XRF), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS)
- Electron and ion spectroscopy (AES, SIMS), and mass spectrometry (GC–MS)
- Typical uses:
- Determining detection limits for hazardous-substance screening (e.g., RoHS testing).
- Environmental monitoring, contamination control, material analysis.
- Establishing decision thresholds in quality control and compliance testing.
- Users include metrology labs, analytical chemists, instrument manufacturers, and accreditation bodies.
Related standards
- ISO 11843 series (Parts 1–4) - general capability of detection principles and linear calibration cases.
- ISO 3534-1 - statistical vocabulary and symbols.
- ISO Guide 30 - reference materials terms.
Keywords: ISO 11843-6:2025, capability of detection, Poisson distribution, normal approximation, critical value, minimum detectable value, detection limit, pulse-counting, spectroscopy, XRF, XRD, GCMS.
Технические детали
- Технический комитет
- ISO/TC 69/SC 6 - Measurement methods and results
- SKU
- ISO 11843-6:2025
Похожие стандарты
Стандарты, упомянутые в описании