Attribute/variable

The adverse event form is fairly standard across clinical trials. The form consists of a list of events for which data are entered as free text and are later coded with a dictionary such as MedDRA and some associated event attribute variables. In just about any clinical trial, an adverse event form very similar to the following sample will be found. 

Two fault categories are associated with quality control—variables and attributes. Variables are those faults that can be measured, usually instrumentally, i.e. dimensional measurements, burst strength, etc. Attributes are those faults which either cannot be accurately assessed (frequently associated with appearance, i.e. visual defects) or can be assessed by go—no go procedures without resorting to accurate measurements. 

Variety parameters Usually there is a set of attributes. A, associated with each Among them, some variables are relevant to variety and thus are defined as variety parameters, P C A. Like attribute variables, parameters can be inherited by child node(s) from a parent node. Different instances of a particular Pp e.g., V, embody the diversity resembled by, and perceived from, product variants. 

The business plan needs to provide projections of aimual production. Based on those estimates and assumed food conversion rates (food conversion is calculated by determining the amount of feed consumed by the animals for each kilogram of weight gain), an estimate of feed costs can be made. For many aquaculture ventures, between 40 and 50% of the variable costs involved in aquaculture can be attributed to feed. 

The unit Kureha operated at Nakoso to process 120,000 metric tons per year of naphtha produces a mix of acetylene and ethylene at a 1 1 ratio. Kureha s development work was directed toward producing ethylene from cmde oil. Their work showed that at extreme operating conditions, 2000°C and short residence time, appreciable acetylene production was possible. In the process, cmde oil or naphtha is sprayed with superheated steam into the specially designed reactor. The steam is superheated to 2000°C in refractory lined, pebble bed regenerative-type heaters. A pair of the heaters are used with countercurrent flows of combustion gas and steam to alternately heat the refractory and produce the superheated steam. In addition to the acetylene and ethylene products, the process produces a variety of by-products including pitch, tars, and oils rich in naphthalene. One of the important attributes of this type of reactor is its abiUty to produce variable quantities of ethylene as a coproduct by dropping the reaction temperature (20—22). 

Molten sodium is injected into the retort at a prescribed rate and the temperature of the system is controlled by adjusting the furnace power or with external cooling. The variables that control the quaUty and physical properties of the powder are the reduction temperature and its uniformity, diluent type and concentration, sodium feed rate, and stirring efficiency. Optimizing a variable for one powder attribute can adversely affect another property. For example, a high reduction temperature tends to favor improved chemical quaUty but lowers the surface area of the powder. 

A capability study is a statistical tool which measures the variations within a manufacturing process. Samples of the product are taken, measured and the variation is compared with a tolerance. This comparison is used to establish how capable the process is in producing the product. Process capability is attributable to a combination of the variability in all of the inputs. Machine capability is calculated when the rest of the inputs are fixed. This means that the process capability is not the same as machine capability. A capability study can be carried out on any of the inputs by fixing all the others. All processes can be described by Figure 1, where the distribution curve for a process shows the variability due to its particular elements. 

The situation is different for other examples—for example, the peptide hormone glucagon and a small peptide, metallothionein, which binds seven cadmium or zinc atoms. Here large discrepancies were found between the structures determined by x-ray diffraction and NMR methods. The differences in the case of glucagon can be attributed to genuine conformational variability under different experimental conditions, whereas the disagreement in the metallothionein case was later shown to be due to an incorrectly determined x-ray structure. A re-examination of the x-ray data of metallothionein gave a structure very similar to that determined by NMR. 

BIN(X) Limits the variable or attribute X to a binary integer value... 

To determine trends in customer satisfaction and dissatisfaction you will need to make regular surveys and plot the results, preferably by particular attributes or variables. The factors will need to include quality characteristics of the product or service as well as delivery performance and price. The surveys could be linked to your improvement programs so that following a change, and allowing sufficient time for the effect to be observed by the customer, customer feedback data could be secured to indicate the effect of the improvement. 

Preliminary process capability studies are those based on measurements collected from one operating run to establish that the process is in statistical control and hence no special causes are present. Studies of unpredictable processes and the determination of associated capability indices have little value. Preliminary studies should show acceptable results for special characteristics before production approval can be given. These studies and associated indices only apply to the measurement of variables and not to attributes (see below). 

The inherent limitations of attribute data prevent their use for preliminary statistical studies since specification values are not measured. Attribute data have only two values (conforming/nonconforming, pass/fail, go/no-go, present/absent) but they can be counted, analyzed, and the results plotted to show variation. Measurement can be based on the fraction defective, such as parts per million (PPM). While variables data follows a distribution curve, attribute data varies in steps since you can t count a fraction. There will either be zero errors or a finite number of errors. 

With attribute data the product either has or has not the ascribed attribute - it can therefore either pass or fail the test. There are no gray areas. Attributes are measured on a go or no-go basis. With variables, the product can be evaluated on a scale of measurement. However, with inspection by attributes we sometimes use an acceptable quality level (AQL) that allows us to ship a certain percent defective in a large batch of product -... 

Where you have required your subcontractors to send a certificate of conformity (CofC) testifying the consignment s conformity with the order, you cannot omit all receiving checks. Once supplier capability has been verified, the C of C allows you to reduce the frequency of incoming checks but not to eliminate them. The C of C should be supported with test results. Therefore you need to impose this requirement in your purchasing documents. However, take care to specify exactly what test results you require and in what format you require them presented, as you could be provided with attribute data when you really want variables data. 

The only statistical techniques which need control are those used to determine the acceptability of a product or service or the capability of a process that produces the product or service. Any activity where you rely on statistical evidence rather than physical measurement is an activity which should be governed by these requirements. The use of recognized techniques is important to the confidence one has in the result. It is similar to the use of measuring equipment that has been calibrated against known standards of accuracy. Unless you actually check every product, measure every attribute or variable you cannot be 100% certain. But that is costly and you can be 99.99% certain by using statistical techniques 99.99% may be sufficiently accurate for your needs. 

Characteristic—A distinguishing feature of a process or its output on which variable or attribute data can be collected. 

Since quantum mechanics allows us to predict, with certainty, the component of the second spin by measuring the same spin component of the first (and remotely positioned) particle - and to do so without in any way disturbing that second particle - BPR s first two assumptions attribute an element of physical reality to the value of any spin component of either particle i.e. the spin components must be determinate. On the other hand, assuming that the particles cannot communicate information any faster than at the speed of light, the only way to stay consistent with BPR s third postulate is to assume the existence of hidden variables. 

None of the procedures outlined can claim any strict justification. Indeed, the deviations of experimental curves from the calculated ones based on simple assumptions can be due in general to a number of causes, some of which were dealt with in Section II.A. A principal ambiguity lies in the choice of whether to treat such departures in terms of either variable Ed or kd, and in the former case often whether the changes in Ed are to be attributed to nonequivalence of adsorption sites, or to lateral interactions between the adsorbed particles, or to yet some other factor (98). 

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