Theory of Sampling and Sampling Practice

1. Definition of Basic Terms and Symbols. 2. A Management Strategy. 3. Fundamental Statistical Concepts. 4. A Logical Introduction to the Components of the Overall Estimation Error. 5. A Logical Introduction to the Notion of Heterogeneity. 6. Heterogeneity of a Zero-Dimensional Lot: Constitution and Distribution Heterogeneities. 7. Heterogeneity of a One-Dimensional Lot: Notion of Variography. 8. Sampling of One-Dimensional Lots: The Continuous Model. 9. Sampling of Zero-Dimensional Lots: 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. 14. The Works of Visman and Ingamells Relevant to the Theory of Sampling. 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. 18. The Increment Materialization Error. 19. Sampling Modes. 20. The Increment Delimitation Error during Exploration, Mining, and Sampling Food and the Environment 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 during Sampling at the Laboratory. 26. The Increment Preparation Errors and the Notion of Sample Integrity. 27. The Increment Weighting Error. 28. The Weighing Error. 29. Sampling for the Determination of the Moisture Content. 30. Peculiarities about the Sampling of Precious Metals. 31. Sampling of Liquid and Solid Wastes and Sampling of the Environment. 32. Solvable and Unsolvable Sampling Problems. 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. 36. An Introduction to Homogenizing Processes. 37. Bed-Blending Techniques. 38 Recommendations for the Design, Installation and Maintenance of Sampling Systems. 39. Introduction to Variography: Notions of Variability and Derivation. 40. Bias Testing: Bias Test Visualization using Pierre Gyâs Approach.