By the end of this course, participants will be able to:
• Concepts involved in the calculation of measurement uncertainty.
• Calculating measurement uncertainty in a practical and pragmatic manner.
• Defining measurement processes.
• Identifying sources of measurement error.
• Selecting appropriate error distributions.
• Using different methods to evaluate measurement uncertainty.
• Measurement uncertainty by practice methods.

The course is designed for chemists, lab technicians, chemical engineers, instrument engineers and lab supervisors/managers.

• Lectures
• Workshop & Work Presentation
• Case Studies and Practical Exercise
• Videos and General Discussions

Module One:

• Introduction
• History & Review
• Chemical Measurement
• Types of methods
• Selection of methods
• Chemical measurement evolution
• Compare duplicate samples results
• Reputability, Reducibility and mean of replicate
• Evaluation of analytical data measurement
• Prerequisites for analytical method validation
• Method Calibration, and Standardization
• Correction of errors and improving Blank

Module Two:

• Calibration Instruments and Measurement methods
• Certificate Reference Material (CRM), choice and preparation
• Degrees of Freedom
• Linearity and Residual analysis in regression
• Blank Correction
• Instruments Calibration and Traceability
• Calibration Procedures, Certificate, and Documentation
• Standard calibration curve
• Standard addition calibration curve
• Internal standard calibration curve
• Characteristic and steps of Method validation
• Selectivity
• Specificity
• Tolerance
• Linearity, Correlation Coefficient
• Accuracy & Precision
• Reliability (Repeatability, Reproducibility)
• Sensitivity, Detection Limit (LOD)
• Dynamic Range (LOQ, LOL, and LUR)
• Robustness

Module Three:

• The Evaluation of Results and Methods
• Errors in chemical measurements
• Systematic, Random, and Gross errors
• Errors in Qualitative and Quantitative Analysis
• Correction of errors and improving accuracy
• Measurement Uncertainty in chemical measurements
• Difference between Error and Uncertainty
• Why we have to used uncertainty in Measurement
• Sources of uncertainty in measurement
• Rationale of uncertainty
• Standard Deviation and Relative Standard Deviation
• Normal Distribution (Gaussian) Curve
• Confidence Limits (Intervals) CL

Module Four:

• Measurement Uncertainty in chemical measurements
• Tiered approach for uncertainty analysis
• Methods for uncertainty characterization
• Recommendations of ISO 17025 for uncertainty
• Steps in Uncertainty Assessment
• Combining Uncertainties
• Expanded uncertainty
• Round Uncertainty
• Procedures for estimating measurement uncertainty
• “Bottom-up” method GUM
• “Top-down” methods
• Monte Carlo method – an alternative to GUM

Module Five:

• Normal Distribution (Gussian Distribution curve)
• Statistical Process Control (SPC) & Control Chart
• Practical exercises for Inter-Laboratory Performance test
• F-test
• T-test (Student’s t Distribution test)
• Q-test
• Z-score
• Practical exercises for Uncertainty& Control Chart
• Manual Calculation for Uncertainty
• Used Excel Function for Uncertainty
• Drawing Control Chart by Excel
• Proficiency Test Calculation
• Significant Figure & Rounding

CDGA attendance certificate will be issued to all attendees completing a minimum of 75% of the total course duration.