3rd Edition

Theory of Sampling and Sampling Practice, Third Edition

By Francis F. Pitard Copyright 2019
726 Pages
by Chapman & Hall

726 Pages
by Chapman & Hall

A step-by-step guide for anyone challenged by the many subtleties of sampling particulate materials. The only comprehensive document merging the famous works of P. Gy, I. Visman, and C.O. Ingamells into a single theory in a logical way - the most advanced book on sampling that can be used by all sampling practitioners around the world.

 

INTRODUCTION AND A MANAGEMENT SRATEGY

1. Definition of Basic Terms and Symbols

2. A Management Strategy

FUNDAMENTAL STATISTICAL CONCEPTS USED IN THE THEORY OF SAMPLING

3. Fundamental Statistical Concepts

4. A Logical Introduction to the Components of the Overall Estimation Error

HETEROGENEITY AND HOMOGENEITY

5. A Logical Introduction to the Notion of Heterogeneity

6. Heterogeneity of a Zero-Dimensional Lot

7. Heterogeneity of a One-Dimensional Lot: Notion of Variography

SAMPLING ERRORS INTRODUCED BY VARIOUS FORMS OF HETEROGENEITY

8. Sampling of one-dimensional lots: the continuous model

9. Zero-dimensional lots and an introduction to the discrete model

10. The Fundamental Sampling Error

11. Minimizing the Fundamental Sampling Error in sampling protocols

12. Other approaches, a strategy, and cardinal rules for the estimation of the variance of FSE

13. The Grouping and Segregation Error

INTEGRATION OF VISMAN AND INGAMELLS’S WORKS INTO THE THEORY OF SAMPLING

14. An introduction to Visman’s work

15. Theoretical, practical, and economic difficulties in sampling for trace constituents

16. From links between Gy and Ingamells to a sampling strategy

17. The In-situ Nugget Effect: a transition between Geostatistics and the Theory of Sampling

THE CAPITAL NOTION OF SAMPLING CORRECTNESS

18. The Increment Materialization Error

19. Sampling modes

20. The Increment Delimitation Error taking place during exploration, mining and when sampling

21. The Increment Delimitation Error at a processing plant

22. The Increment Delimitation Error during sampling at the laboratory

23. The Increment Extraction Error during exploration and mining

24. The Increment Extraction Error during sampling in a processing plant

25. The Increment Extraction Error taking place at the laboratory

26. The Increment Preparation Error and the notion of sampling integrity

THE INCREMENT WEIGHTING AND WEIGHING ERRORS

27. The Increment Weighting Error

28. The Weighing Error

REVIEW OF SOME NOTORIOUS SAMPLING PROBLEMS

29. Sampling for the determination of the moisture content

30. Peculiarities about the sampling of precious metals and other very heavy minerals Introduction

31. Sampling of liquid and solid wastes and sampling of the environment Introduction

32. Solvable and unsolvable sampling problems

CHRONOSTATISTICS

33. A strategy to take better advantage of existing chronological data

34. The use of the variogram to elaborate meaningful process control charts

35. Case studies where variography is an effective tool to discover and quantify structural problems

HOMOGENIZATION

36. An introduction to homogenizing processes

37. Bed-blending techniques

RECOMMENDATIONS TO MANUFACTURERS OF SAMPLING EQUIPMENT AND TO ENGINEERING FIRMS

38. Recommendations for the design, installation and maintenance of sampling systems

Biography

Dr. Pitard is a well-known authority on sampling theory and practice. He has a Doctorate of Technologies from the University of Aalborg. He is the recipient of the famous Pierre Gy’s Gold Medal for excellence in promoting and his teaching of the Theory of Sampling all around the world.

"The unique feature of this well written comprehensive book is its step-by-step guidance in all thirty-eight chapters under twelve parts. Basic knowledge of calculus, matrix theory and mathematical statistics is essential to comprehend this book. ... I enjoyed reading this book. I recommend this book to engineers, geologists, chemists, environmental scientists, instructor of statistics courses and computing professionals."
-Ramalingam Shanmugam in Journal of Statistical Computation and Simulation, June 2020