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By Patricia L. Smith

ISBN-10: 0898714737

ISBN-13: 9780898714739

This knowledge may also help statisticians use sampling innovations for bulk-material samples that aren't made from well-defined devices. It tells what to appear for in sampling units and approaches to procure present samples from bulk fabrics, offers sampling directions that may be utilized instantly, and exhibits tips to learn protocols to discover sampling difficulties. there's an advent to the information of Pierre Gy in daily language, with intuitive factors, and examples of straightforward experiments readers can practice to appreciate rules. For graduate scholars in classes on sampling, in addition to experts in records, environmental technology, and business and chemical engineering. Smith is a statistician, facts analyst, and approach development professional

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Extra resources for A Primer for Sampling Solids, Liquids, and Gases: Based on the Seven Sampling Errors of Pierre Gy

Sample text

This is not practical, however, when the material flows very fast and splashes or is hazardous. Solids moving along a conveyor belt provide the opportunity for correct, one-dimensional, cross-stream sampling before the material collects as a threedimensional lot where the principle of correct sampling cannot be followed. In both of these cases, we also have the fourth dimension, time, where sampling frequency and process variation add complicating elements. These will be explored in detail in Chapter 4.

Some details on the derivation and application of this formula are given in Appendix B. 5 Reducing the variance of the fundamental error (FE) We can reduce Var(FE) in several ways to get more consistently representative samples. 2) we see that the sample mass MS is inversely proportional to Var(FE). Thus, assuming the sampling is random, increasing the quantity MS of material in the physical sample will reduce Var(FE). Also, particle size is directly proportional to Var(FE). 5 We must take care, however, to preserve the integrity of the sample so that the component of interest is not left in the grinding wheels or smeared on the side of the mortar.

Particle size is directly proportional to the sampling variation. Thus, reducing the particle size will reduce the theoretical sampling variation, even when the sample mass is not increased. 4. Mix the material. This reduces the lot segregation and consequently the inflationary effect on sampling variation resulting from selecting groups rather than individual units. 1 Representative sampling As discussed in Chapter 1, we would like to obtain samples that are representative of the entire lot. That way we will know exactly (or at least within the analytical measurement) the values of the properties of interest.

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A Primer for Sampling Solids, Liquids, and Gases: Based on the Seven Sampling Errors of Pierre Gy by Patricia L. Smith

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