By the end of this course delegates will be able to:
It is necessary to balance cost of QC & QA against the benefit in reducing quality failures to an acceptable (non-zero) level, you will learn how develop laboratory documents and quality. Attendees will receive practical instructions on the development, implementation and long-term maintenance of an effective laboratory quality system.

Laboratory supervisors, chemists, and senior technicians working in QA/QC

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

Module Two:

• Method Calibration, and Standardization
• Correction of errors and improving Blank
• 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

Module Three:

• 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
• The Evaluation of Results and Methods
• Type of errors in chemical measurements
• Systematic, Random, and Gross errors
• Errors in Qualitative and Quantitative Analysis
• Correction of errors and improving accuracy
• Correction of errors and improving accuracy

Module Four:

• Measurement Uncertainty in chemical measurements
• Difference between Error and Uncertainty
• Sources of uncertainty in measurement
• Recommendations of ISO 17025 for uncertainty
• Procedures for estimating measurement uncertainty
• “Bottom-up” method GUM
• “Top-down” methods
• Monte Carlo method – an alternative to GUM
• Normal Distribution (Gussian Distribution curve)
• Statistical Process Control (SPC) & Control Chart

Module Five:

• 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
• Quality Assurance and Audit Program
• Significant Figure & Rounding
• Reporting Analytical results and Archives
• Laboratory Certification

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