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Representative Process Sampling for Reliable Data Analysis—a Tutorial by Lars Petersen; Kim H. Esbensen is a Chemistry article available to read on EtoBox.
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## Abstract Process sampling of moving streams of particulate matter, fluids and slurries (over time or space) or stationary one‐dimensional (1‐D) lots is often carried out according to existing tradition or protocol not taking the theory of sampling (TOS) into account. In many situations, sampling errors (sampling variances) can be reduced greatly however, and sampling biases can be eliminated completely, by respecting a simple set of rules and guidelines provided by TOS. A systematic approach for description of process heterogeneity furnishes in‐depth knowledge about the specific variability of any 1‐D lot. The __variogram__ and its derived auxiliary functions together with a set of error generating functions provide critical information on:—process variation over time or space,—the number of extracted increments to composite into a final, optimal sample,—the frequency with which to extract increments—and which sampling scheme will be optimal (random, stratified random or systematic selection). In addition variography will delineate cyclic behaviors as well as long‐term trends thereby ensuring that future sampling will not accidentally be performed with a sampling rate coincident
Who reads Representative Process Sampling for Reliable Data Analysis—a Tutorial?
It is typically read by researchers, students, and practitioners in Chemistry.
- Author
- Lars Petersen; Kim H. Esbensen
- Publisher
- John Wiley and Sons; Wiley (John Wiley & Sons); John Wiley & Sons Ltd.; Wiley (ISSN 0886-9383)
- Published
- 2005
- Language
- EN
- Field
- Chemistry (Physical Sciences)