The Planning of Experiments

The planning of good experiments for an in situ spectroscopic homogeneous catalytic study is a non-trivial matter. Indeed, the number and quality of the pure component spectra recovered are strongly dependent on the experimental planning. 

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C. Lipson and N. J. Sheth, Statistica/Design andAna/ysis of Engineering Experiments, McGraw-HiU, New York, 1972. "This book is written in a relatively simple style so that a reader with a moderate knowledge of mathematics may foUow the subject matter. No prior knowledge of statistics is necessary." Appreciably more discussion is devoted to statistical analysis than to the planning of experiments. Some relatively nonstandard subjects (for an introductory text), such as accelerated experiments, fatigue experiments, and renewal analysis are also included. 

This author is pleased to repeat that his views on the role of esters as propagating species in cationoid polymerisations are surely open to improvement and refinement, but that they are a more useful guide to the interpretation of phenomena and the planning of experiments, than the views of the Commentator. The criterion of a successful scientific theory is heuristic utility. 

There is a broad field of statistics which is devoted to the planning of experiments in a way that considers ... 

The aim of this chapter is to demonstrate suitable protocols for the planning of experiments and the analysis of the data. The important question to keep in mind is, What is the purpose of the experiment and what do I propose as the outcome Usually, defining the question takes greater effort than performing any analysis. Defining the question is more technically termed defining the research hypothesis, following which the statistical tools can be used to determine whether the stated hypothesis is found to be true. 

This section is organized into two subsections. In the first, we will illustrate the notion of variance component estimation through an example of a nested or hierarchical data collection scheme. In the second, we will discuss some general considerations in the planning of experiments to detail the pattern of influence of factors on responses, consider so-called factorial and fractional factorial experimental designs, illustrate response surface fitting and... 

In these situations, we cannot start the analysis of data without separating the effect of the external systematic influence from the unprocessed new data. In other words, we must separate the variations due to the actions of some factors with systematic influences from the original data. For this purpose, the methods of Latin squares and of effects of unification of factors have been developed in the plan of experiments. 

Chemometrics has been defined as the chemical discipline that uses mathematical and statistical methods to design or select optimal measurement procedures and experiments and to provide maximum chemical information by analysing chemical data (Kowalski, 1978). It is a relatively new discipline that assists with (i) the planning of experiments, and (ii) the manipulation and interpretation of large data sets. Some aspects of chemometrics can be done using an appropriate speadsheet but the majority of applications require the use of dedicated software. The fundamental principles of most of the processes involved in chemometrics are those of statistics. You are therefore advised to become familiar with the material in Chapters 40 and 41 before proceeding. 

Progress in research depends upon development of technique. No matter how important the cerebral element may be in the planning of experiments, a tentative hypothesis cannot be converted into an accepted fact unless there is adequate consciousness of the scope and limitation of existing techniques moreover, the results may be meaningless or even positively misleading if the technical know how is inadequate. 

If the plan of experiments is rich (number of measurement n = w + 1, where w is the number of factors) and symmetrical (sum of the values of each independent variable, including the repeatable values during experiment, is equal to zero), and the variables themselves are orthogonal (i.e., independent), then the regression... 

The planning of experiments on three-component diffusion for the determination of diffusion coefficients and frictions, in a way which makes full use of the available instrumental accuracy, is a question of considerable complexity. There are three main t5rpes of experiment to consider, viz., two components are dilute (e.g. 1 and 3), one is dilute (e.g. 2), or none is dilute. The latter requires the full equations reported above. The first case is of interest as it enables us to determine the special flow interaction between two components which arises at low concentrations of the components, and which is therefore simplest to interpret... 

W e hope that this review wiU be helpful for the planning of experiments, choice of probe molecules, and interpretation of the results, not only for beginners but also for the experienced scientists in the field. 

Analysis of the kinetie model behavior, model update, and the planning of experiments aimed at updating the model. 

Whenever possible the basic molecular events of physiological processes are studied in detail in solutions either in parallel with, or as a guide to, experiments on the organized system. For example, the study of the reactions of myosin and the associated proteins of the contractile cycle, by the methods used for the investigation of mechanisms of soluble enzymes (see section S.l), has helped in the planning of experiments and in the interpretation of the events observed in muscle fibres. The most useful methods for kinetic studies on physiological functions are those which can be applied to systems at different levels of organization. We shall return to them at the end of this chapter. 

In the preceding we have discussed the planning of experiments with a view of delineating the effect of gas phase mass transfer and chemical kinetics. All that remains is to comment briefly on pore diffusion. 

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