Measurement Uncertainty for Analytical Testing

Programme Summary

Develop defensible uncertainty estimates for quantitative analytical results using available laboratory evidence. Participants build measurement models, evaluate precision and bias contributions, and avoid double counting when combining information. Case exercises translate budgets into appropriate expanded uncertainty and reporting statements, helping laboratories explain result reliability and target improvements where they will have the greatest practical effect.

Training Objectives

1 Connect uncertainty with analytical decision quality; 2 Identify significant sources of measurement uncertainty; 3 Select appropriate analytical uncertainty evaluation approaches; 4 Combine evidence without duplicating uncertainty contributions; 5 Communicate estimates and improvement priorities clearly.

Learning Outcomes

1 Define a measurand and uncertainty model; 2 Construct an analytical uncertainty budget; 3 Convert contributions into standard uncertainties; 4 Calculate and report expanded measurement uncertainty; 5 Identify evidence needing further technical investigation.

Target Audience

Analytical Chemists; Laboratory Quality Managers; Technical Managers; Validation Specialists; Senior Laboratory Analysts.

Target Industries

Independent Testing Laboratories; Chemical Testing Laboratories; Food Testing Laboratories; Environmental Testing Laboratories; Materials Testing Laboratories; Industrial Quality Laboratories.

Course Contents

• Module 1 Uncertainty and Analytical Decisions: Measurand specification and result interpretation; Error uncertainty and bias distinctions; Fitness for purpose and target uncertainty.
• Module 2 Building the Measurement Model: Analytical equation and influencing quantities; Concentration dilution and recovery relationships; Mapping significant uncertainty sources.
• Module 3 Statistical Evidence: Standard deviations and standard errors; Repeatability and intermediate precision evidence; Degrees of freedom and limited datasets.
• Module 4 Reference and Calibration Evidence: Certificates and stated coverage factors; Calibration curve uncertainty and residuals; Reference material values and matrix relevance.
• Module 5 Precision Based Evaluation: Within laboratory reproducibility evidence; Concentration dependent precision patterns; Representativeness of routine operating conditions.
• Module 6 Bias and Recovery Contributions: Reference material comparisons and uncertainty; Recovery correction and associated uncertainty; Avoiding duplicated bias and precision terms.
• Module 7 Type B Evaluations: Resolution tolerances and stated limits; Selecting justified probability distributions; Converting limits to standard uncertainties.
• Module 8 Combining Contributions: Sensitivity coefficients and unit consistency; Covariance and dependent input quantities; Combined standard uncertainty calculation.
• Module 9 Expanded Uncertainty: Coverage factor selection and limitations; Effective degrees of freedom awareness; Reporting significant figures and coverage.
• Module 10 Special Analytical Considerations: Low concentrations and asymmetric intervals; Sampling contributions and scope boundaries; Qualitative testing and applicability limits.
• Module 11 Review and Maintenance: Sensitivity review and dominant contributors; Changes requiring budget reassessment; Technical review and controlled records.
• Module 12 Analytical Budget Workshop: Constructing a supported uncertainty budget; Checking calculation and reporting consistency; Presenting limitations and improvement actions.

Assessment

• 60 single best answer questions, including applied scenarios; one mark per question.
• 90 minute invigilated digital examination with identity verification. Approved accessibility adjustments preserve the assessed competence.
• Supplied reference pack and calculator permitted; external internet and AI prohibited.
• Individual applied assessment (45 minutes): Build and review an analytical uncertainty budget from supplied data; calculate expanded uncertainty and write a technically consistent reporting statement.
• Assessment criteria: Sound contribution selection and evidence; Correct combination and coverage calculation; Clear reporting and limitation recognition.
• Pass each component separately: 45/60 written marks (75%) and at least 70% on the applied task.
• Individual results and feedback are provided. One reassessment may follow coaching under the published enrolment terms.

Certification

• Successful learners receive a TQCSI Arabia digital Certificate of Successful Completion.
• The certificate records the learner name, exact programme title, teaching hours, completion date and unique verification reference.
• Verified identity, full attendance and separate written and applied passes are required; all mandatory critical criteria must be met.
• Proposed issue target: within 30 calendar days of approved results and settlement of applicable fees.
• Records analytical uncertainty evaluation skills; laboratory approval and discipline specific technical authorisation remain separate decisions.
• Attendance confirmation may record completed hours for unsuccessful learners; it does not certify successful completion.

Programme Profile

Number of daysNumber of daysNumber of days

333

Total teaching hoursTotal teaching hoursTotal teaching hours

18 hours; breaks, pre course work and formal final assessments excluded.18 hours; breaks, pre course work and formal final assessments excluded.18 hours; breaks, pre course work and formal final assessments excluded.

Delegates allowedDelegates allowedDelegates allowed

Maximum 16 delegates.Maximum 16 delegates.Maximum 16 delegates.

Training prerequisitesTraining prerequisitesTraining prerequisites

Quantitative analytical experience, basic statistics and spreadsheet competence are required. Familiarity with method validation and quality control data is recommended.Quantitative analytical experience, basic statistics and spreadsheet competence are required. Familiarity with method validation and quality control data is recommended.Quantitative analytical experience, basic statistics and spreadsheet competence are required. Familiarity with method validation and quality control data is recommended.

Pre course assignment and assessmentPre course assignment and assessmentPre course assignment and assessment

Complete a 30-minute statistics diagnostic and review supplied precision, recovery and calibration data.Complete a 30-minute statistics diagnostic and review supplied precision, recovery and calibration data.Complete a 30-minute statistics diagnostic and review supplied precision, recovery and calibration data.

End of course assessmentEnd of course assessmentEnd of course assessment

60 question written exam (90 minutes) and individual applied task (45 minutes).60 question written exam (90 minutes) and individual applied task (45 minutes).60 question written exam (90 minutes) and individual applied task (45 minutes).

Passing criteriaPassing criteriaPassing criteria

75% written and 70% applied, passed separately; full attendance.75% written and 70% applied, passed separately; full attendance.75% written and 70% applied, passed separately; full attendance.