Statistics history

Validation of the Component Manufacturing Variability Risk, is essential to CA in determining estimates for component characteristics at the design stage. Collecting component parts from various industrial sources with known statistical histories was central to this. The components were taken from a number... 

The Bureau of the Census also published a statistical history of the growth of plastics through 1939 24) based on data from the Census of Manufactures. ... 

But, no statistical, historical performance measurement system can assess the quality of safety in place that encompasses low probability-high consequence incidents since such events seldom appear in the statistical history. Example A risk assessment concludes that a defined catastrophic event, one that has not happened and is not represented in the statistical base, has an occurrence probability of once in 200 plant operating years.)... 

Statistical, historical performance measurement systems cannot accurately encompass the potential for low probability-severe consequence events occurring since such events seldom appear in the statistical history. 

A statistical history supports proposing that safety professionals pay particular attention to the characteristics of incidents resulting in serious injuries, particularly with respect to the nature of work being done and the job titles of injured personnel. 

Therefore, when using the severity and probability techniques simultaneously, hazards can be examined, qualified, addressed, and resolved based upon the hazardous severity of a potential outcome and the likelihood that such an outcome will occur. For example, while an aircraft collision in midair would unarguably be classified as a Category I mishap (catastrophic), the hazard probability would fall into the Level D (remote) classification based upon statistical history of midair collision occurrence. The system safety effort in this case would require specific, but relatively minimal... 

Our purpose in this introduction is not to trace the history of polymer chemistry beyond the sketchy version above, instead, the objective is to introduce the concept of polymer chains which is the cornerstone of all polymer chemistry. In the next few sections we shall introduce some of the categories of chains, some of the reactions that produce them, and some aspects of isomerism which multiply their possibilities. A common feature of all of the synthetic polymerization reactions is the random nature of the polymerization steps. Likewise, the twists and turns the molecule can undergo along the backbone of the chain produce shapes which are only describable as averages. As a consequence of these considerations, another important part of this chapter is an introduction to some of the statistical concepts which also play a central role in polymer chemistry. 

As usually the statistical properties of the experimental data are poorly known, nobody can guarantee that the standard statistical procedures give the tmstworthy results. The history of chemical data treatment exemplifies impressively the persistent stmggle for obtaining more and more reliable meaningful information from the experimental data. 

The beginnings of the enormous field of solid-state physics were concisely set out in a fascinating series of recollections by some of the pioneers at a Royal Society Symposium (Mott 1980), with the participation of a number of professional historians of science, and in much greater detail in a large, impressive book by a number of historians (Hoddeson et al. 1992), dealing in depth with such histories as the roots of solid-state physics in the years before quantum mechanics, the quantum theory of metals and band theory, point defects and colour centres, magnetism, mechanical behaviour of solids, semiconductor physics and critical statistical theory. 

The Seismic Safety Margins Research Program developed a computer code called SMACS (Seismic Methodology Analysis Chain with Statistics) for calculating the seismic responses of structures, systems, and components. This code links the seismic input as ensembles of acceleration time histories with the calculations of the soil-structure interactions, the responses of major structures, and the responses of subsystems. Since uses a multi-support approach to perform the time-history response calculations for piping subsystems, the correlations between component responses can be handled explicitly. SMACS is an example of the codes that are available for calculating seismic response for PSA purposes. 

Representativeness can be examined from two aspects statistical and deterministic. Any statistical test of representativeness is lacking becau.se many histories are needed for statistical significance. In the absence of this, PSAs use statistical methods to synthesize data to represent the equipment, operation, and maintenance. How well this represents the plant being modeled is not known. Deterministic representativeness can be answered by full-scale tests on like equipment. Such is the responsibility of the NSSS vendor, but for economic reasons, recourse to simplillcd and scaled models is often necessary. System success criteria for a PSA may be taken from the FSAR which may have a conservative bias for licensing. Realism is more expensive than conservatism. 

Because the number of microstates available to the system depends only on its current state, not on its past history, W depends only on the current state of the system, and therefore the statistical entropy does, too. 

An obituary of Zentralblatt by Weiske, which gives its history and statistical data about its abstracts and indexes, was published in the April 1973 issue of Chem. Ber. (pp. I-XVI). 

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