Module 1 — Essential Metrology Concepts

• Measurement accuracy
• Measurement trueness
• Measurement precision
• Precision versus trueness
• Standard deviation and relative standard deviation
• Repeatability
• Intermediate precision
• Reproducibility
• Repeatability and reproducibility limits
• Factors affecting precision
• Measurement bias

Module 2 — Method Validation & Verification

• What is verification?
• What is validation?
• Validation versus verification
• Fitness for purpose
• When validation is required
• Verification of standard methods
• Standard methods used outside their intended scope
• Modified standard methods
• Non-standard methods
• Laboratory-developed methods
• Validation across concentration ranges and matrices
• Method performance characteristics and acceptance criteria

Module 3 — Verification of Precision

• Verification of standard-method performance
• Comparison of laboratory precision with published method performance
• Repeatability standard deviation
• Variance comparison using the F-test
• Interpretation of statistical results
• Worked laboratory examples

Exercise 1 — Verification of Repeatability

Module 4 — Evaluation of Trueness, Bias & Recovery

• Measurement bias
• Approaches to evaluating trueness
• Use of certified reference materials and reference materials
• Reference measurement methods
• Recovery studies
• Calculation and interpretation of recovery

Exercise 2 — Recovery Study

Module 5 — Statistical Significance Testing

• Purpose of statistical significance testing
• Null and alternative hypotheses
• Confidence levels
• One-tailed and two-tailed tests
• Comparison of a mean with a reference value
• Comparison of two independent datasets
• Variance comparison
• t-tests and interpretation of results

Exercise 3 — Significance Testing

Paired Comparisons

• Comparison of two methods across the same samples
• Calculation and interpretation of paired differences
• Paired t-test approach

Exercise 4 — Paired Test

Module 6 — Calibration & Linearity

• Principles of calibration
• Designing a calibration study
• Number and distribution of calibration standards
• Replicate measurements
• Calibration range
• Matrix considerations
• Linear regression
• Least-squares regression
• Residuals and residual plots
• Identification of potential outliers
• Residual standard deviation
• Evaluation of slope and intercept
• Using Excel LINEST for regression statistics

Exercise 5 — Calibration & Linearity

Module 7 — Limit of Detection & Limit of Quantification

• Principles of detection and quantification limits
• Graphical approaches
• Blank-based estimation
• Low-level control samples
• Calibration-curve approaches
• Selection of suitable samples
• Replication considerations
• Practical interpretation of LOD and LOQ

Module 8 — Robustness

• Purpose of robustness evaluation
• Identifying influential method variables
• Evaluating minor changes in test conditions
• Examples of factors affecting method performance
• Introduction to experimental design for robustness evaluation
• Plackett–Burman experimental design
• Calculation of factor effects
• Statistical interpretation of factor effects
• Worked pH example

Exercise 6 — Robustness