Terminology, sampling

The following paper provides a general introduction to the terminology used in describing sampling. 

Finally, a word on terminology. Many AI methods learn by inspecting examples, which come in a variety of forms. They might comprise a set of infrared spectra of different samples, the abstracts from a large number of scientific articles, a set of solid materials defined by their composition and their emission spectrum at high temperature, or the results from a series of medical tests. In this text, we refer to these examples, no matter what their nature, as "sample patterns."... 

In this chapter we use the terms precision and accuracy in relation to the finite sampling variance and bias, respectively. Also, we describe the overall quality of an estimator - the mean square error - by the term reliability. Note the difference between our terminology and that in some statistics literature where accuracy is used to describe the overall quality (i.e., the reliability in this chapter). The decomposition of the error into the variance and bias allows us to use different approaches for studying the behavior of each term. 

The terminology used in this Standard is slightly different from the others in that it is appropriate for the particular discipline. For example, the term, referral laboratories in paragraph 4.5 of ISO 15189 is used in a slightly different sense to the comparable clause in ISO/IEC 17025. Included in this section are consultants who may provide a second opinion. If the referral laboratory is an external laboratory, to which samples are submitted for a supplementary or confirmatory examination procedure and report, it is much the same as a contract laboratory in ISO/IEC 17025. There is an extra Annex in this Standard which covers the ethics applicable to laboratory medicine. 

While the broad mission of the National Bureau of Standards was concerned with standard reference materials, Dr. Isbell centered the work of his laboratory on his long interest in the carbohydrates and on the use of physical methods in their characterization. Infrared spectroscopy had shown promise in providing structural and conformational information on carbohydrates and their derivatives, and Isbell invited Tipson to conduct detailed infrared studies on the extensive collection of carbohydrate samples maintained by Isbell. The series of publications that rapidly resulted furnished a basis for assigning conformations to pyranoid sugars and their derivatives. Although this work was later to be overshadowed by application of the much more powerful technique of nuclear magnetic resonance spectroscopy, the Isbell— Tipson work helped to define the molecular shapes involved and the terminology required for their description. 

To simplify terminology of axial systems, gzz is defined to be g(l (the g-value observed with the symmetry axis of Cu + parallel to the applied field), and gxx (= gyy) is defined to be gA (the g-value observed with the symmetry axis perpendicular to the applied field). An elongated z-axis (depicted in Figure 11 for Cu(H20)5 +) results in gjj > gj. For axially symmetric Cu + rigidly bound in a crystal, the g-value can then vary between the minimum (gj.) and maximum (g(,), depending on orientation of the crystal within the magnetic field. However, for axial Cu + bound in a powdered clay sample, all possible orientations, and therefore all g-values between gA and gj are represented in the "powder" spectrum. Therefore, electron spin resonance occurs only for field values, H, between Hjj and H, where ... 

The terminology error invariably refers to the difference in the numerical values between a measured value and the true value. It has become universally accepted in methods of comparison that the percentage composition of a standard sample provided and certified by the National Institute of Standards and Technology (NIST) or the British Pharmacopoea Chemical Reference Substance (BPCRS) or the European Pharmacopoea... 

OFDs can be divided into two subclasses (1) optical fiber chemical detectors (OFCD) which detect the presence of chemical species in samples, and (2) optical fiber biomolecular detectors (OFBD) which detect biomolecules in samples. Each subclass can be divided further into probes and sensors, and bioprobes and biosensors, respectively. As a result of the rapid expansion of optical research, these terms have not been clearly defined and to date, the terms probe and sensof have been used synonymously in the literature. As the number of publications increases, the terminology should be clarified. Although both probes and sensors serve to detect chemicals in samples, they are not identical. The same situation exists with bioprobes and biosensors. Simply, probes and bioprobes are irreversible to the analyte s presence, whereas sensors and biosensors monitor compounds reversibly and continuously. 

This approach is commonly employed for bound zeolites. In this manner the relative amount of crystalline zeolite present can be determined. As usually implemented, the method provides a number that is the ratio of intensities for peaks in the diffraction pattern of the sample of interest to the intensity of the same peaks in the pattern of a reference zeolite. Since the intensity ratio is often expressed as a percentage, it is commonly referred to as percent zeolite crystallinity. The better terminology is relative amount of crystalline zeolite compared to a specific reference. 

This new terminology is proposed jointly in the present publication and in Pitard Pierre Gy s Theory of Sampling and C.O. IngamelTs Poisson Process Approach — Pathways to Representative SampUng and Appropriate Industrial Standards . Doctoral thesis, Aalborg University, campus Esbjerg (2009). ISBN 978-87-7606-032-9. 

In both ECD and ETD experimental approaches, a positively charged sample of a polypeptide enters the gas phase (usually via electrospray), after which ions of specific mass to charge ratio are selected. Usually, the positive charging is induced by subjecting the solution-phase sample to acidic conditions prior to electrospray. An example of a relatively simple polypeptide is shown in Figure 1 as a means for introducing several concepts and terminology. 

The second difference is that the correlations between samples are calculated rather than the correlations between elements. In the terminology of Rozett and Peterson ( ), the correlation between elements would be an R analysis while the correlation between samples would be a Q analysis. Thus, the applications of factor analysis discussed above are R analyses. Imbrle and Van Andel ( 6) and Miesch (J 7) have found Q-mode analysis more useful for interpreting geological data. Rozett and Peterson (J ) compared the two methods for mass spectrometric data and concluded that the Q-mode analysis provided more significant informtlon. Thus, a Q-mode analysis on the correlation about the origin matrix for correlations between samples has been made (18,19) for aerosol composition data from Boston and St. Louis. 

---