The third edition of Quality Assurance and Quality Control in the Analytical Chemical Laboratory: A Practical Approach defines the tools used in QA/QC, especially the application of statistical tools during analytical data treatment.
The third edition of Quality Assurance and Quality Control in the Analytical Chemical Laboratory: A Practical Approach defines the tools used in QA/QC, especially the application of statistical tools during analytical data treatment. Clearly written and logically organized, this well-loved volume takes a generic approach applicable to any field of analysis. The authors begin with the theory behind quality control systems, then detail validation parameter measurements, the use of statistical tests, counting the margin of error, uncertainty estimation, traceability, reference materials, proficiency tests, and method validation. The new edition contains fully updated references throughout and includes new information on CRMs and PTs. A new chapter covers calibration and contains numerous new examples, and the subject of accreditation is expanded.
· Fully updated and revised references.
· New computational examples and solution problems.
· New chapter on Calibration and expanded coverage of Accreditation.
· A practical approach applicable to any field of analysis.
LIST OF ABBREVIATIONS
1. BASIC NOTIONS OF STATISTICS
1.1. Introduction
1.2. Distributions of random variables
1.2.1. Characterization of distributions
1.3. Measures of location
1.4. Measures of dispersion
1.5. Measures of asymmetry
1.6. Measures of concentration
1.7. Statistical hypothesis testing
1.8. Statistical tests
1.8.1 Confidence interval method
1.8.2. Critical range method
1.8.3. Dixons Q test
1.8.4. Chi-Square test
1.8.5. Snedecors F test
1.8.6. Hartleys Fmax test
1.8.7. Bartletts test
1.8.8. Morgans test
1.8.9. Students t test
1.8.10. Cochran-Cox test
1.8.11. Aspin-Welch test
1.8.12. Cochrans test
1.8.13. Grubbs test
1.8.14. Hampels test
1.8.15. Z-Score
1.8.16. En Score
1.8.17. Mandels test
1.8.18. Kolmogorov-Smirnov test
1.9. Linear regression
1.10. Significant Digits. Rules of Rounding.
1.11. References
2. QUALITY OF ANALYTICAL RESULTS
2.1. Definitions
2.2. Introduction
2.3. Quality assurance system
2.4. Conclusions
2.5. References
3. INTERNAL QUALITY CONTROL
3.1. Definitions
3.2. Introduction
3.3. Quality control in the laboratory
3.4. Control charts 3.4.1. Shewhart charts
3.4.2. Shewhart chart preparation
3.4.3. Shewhart chart analysis
3.4.4. Types of control charts
3.4.5.Control samples
3.5. Conclusion
3.6. References
4. TRACEABILITY
4.1. Definitions
4.2. Introduction
4.3. The role of traceability in QA/QC system
4.4. Conclusion
4.5. References
5. UNCERTAINTY
5.1. Definitions
5.2. Introduction
5.3. Methods of estimating of measurement uncertainty
5.3.1. Procedure for estimating the measurement uncertainty according to GUM
5.4. Tools used for uncertainty estimation
5.5. Uncertainty and confidence interval
5.6. Calibration uncertainty
5.7. Conclusion
5.8. References
6. REFERENCE MATERIALS
6.1. Definitions
6.2. Introduction
6.3. Parameters which characterize RMs
6.3.1. General information
6.3.2. Representativeness 6.3.3. Homogeneity 6.3.4. Stability 6.3.5.
Certified value
6.4. Production of CRMs requirements (ISO 17034)
6.5. Practical application of CRM
6.6. Conclusion
6.7. References
7. INTERLABORATORY COMPARISIONS
7.1. Definitions
7.2. Introduction
7.3. Classification of interlaboratory studies
7.4. Characteristics and organization of interlaboratory comparisons
7.5. The presentation of interlaboratory comparison results. Statistical
analysis in interlaboratory comparisons
7.5.1. Comparisons of results obtained using various procedures
7.5.2. Comparison of the measurement results obtained in a two-level study
(for two samples with various analyte concentrations)
7.6. Organisation of PTs requirements (ISO 17043)
7.7. Conclusions
7.8. References
8. CALIBRATION
8.1. Introduction
8.2. Types of calibration
8.3. Calibration techniques
8.3.1. Single standard technique
8.3.2. Bracketing solutions technique
8.3.3. Calibration curve technique
8.3.4. Standard addition technique
8.3.5. Multiple standard addition technique
8.3.6. Internal standard technique
8.3.6.1. Isotope Dilution Mass Spectrometry (IDMS) technique
8.4. Conclusions
8.5. References
9. METHOD VALIDATION
9.1. Introduction
9.2. Characterization of validation parameters
9.2.1. Selectivity
9.2.2. Linearity
9.2.3. Limit of Detection and Limit of Quantitation
9.2.4. Range
9.2.5. Sensitivity
9.2.6. Precision
9.2.6.1. Manners of estimating the standard deviation
9.2.7. Accuracy and Trueness
9.2.7.1. Measurement Errors
9.2.8. Robustness and ruggedness
9.2.9. Uncertainty
9.3. Conclusions
9.4. References
10. METHOD EQUIVALENCE
10.1. Introduction
10.2. Ways of equivalence demonstration
10.2.1. Difference testing
10.2.2. Equivalence testing
10.2.3. Regression analysis testing
10.3. Conclusions
10.4. References
APPENDIX
Piotr Konieczka is Professor at Gdask University of Technology, where he is Head of the Department of Analytical Chemistry. He has co-authored 113 publications, 8 books and holds 1 patent. His research interests are environmental pollution analysis, trace analysis, in particular analysis of heavy metal content using spectroscopic techniques, as well as chemical statistics and metrology, as well as control and quality assurance of analytical measurement results, including aspects related to the production and use of certified reference materials (CRM) and the organization and development of proficiency test results (PT).
