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Randomized experiments plan

Statistical and algebraic methods, too, can be classed as either rugged or not they are rugged when algorithms are chosen that on repetition of the experiment do not get derailed by the random analytical error inherent in every measurement,i° 433 is, when similar coefficients are found for the mathematical model, and equivalent conclusions are drawn. Obviously, the choice of the fitted model plays a pivotal role. If a model is to be fitted by means of an iterative algorithm, the initial guess for the coefficients should not be too critical. In a simple calculation a combination of numbers and truncation errors might lead to a division by zero and crash the computer. If the data evaluation scheme is such that errors of this type could occur, the validation plan must make provisions to test this aspect. [Pg.146]

Each group of experiments should be pre-planned. Perhaps multiple batch experiments, semi-batch or both can be conveniently used. The initial conditions for the batch runs and the steps of the semi-batch runs can be chosen randomly or in a judicious manner. The really important issue is that the mole ratios of any two reagents should never be held constant in a group this constitutes a co-linearity induced by the experimentalist. It can be noted that each perturbation in a semibatch experiment limits the future accessible region of composition space so planning is advisable. [Pg.168]

In the simultaneous approach the experiments are planned beforehand (preferably using experimental design techniques) and performed randomly. With RSM techniques the obtained experimental data can be used to model the quality criterion as a function of the design variables. Then an optimal setting of the design variables can be calculated. All the optimization experiments described in this book are using the simultaneous approach. The simultaneous approach uses in almost all... [Pg.6]

A Taguchi experimental plan with two levels and four variables (temperature, exposure time, decompression rate, and reduced density) was adopted. The experimental plan, covering the variable ranges commonly usedfor transesterification reactions (1), is presented inTable 1. The experiments were accomplished randomly, and duplicate runs were carried out for all experimental conditions leading to an average reproducibility better than 5%. The activity loss was then modeled empirically in order to determine the influence of the process variables on main and cross-interaction parameters. [Pg.184]

Nine factors that influence the choice of themes can be identified in the interviews experience, the media, unfortunate developments, special commissions from the Government, budget documents, production of statistics, tips from other authorities, tradition and annual activity plans. The choice of inspection objects is influenced by eight corresponding factors random sampling, what you can find, geographical site, hearsay, long time ago, piecework, self-prioritisation and previous problem kids.2... [Pg.328]

A real process is frequently influenced by non-commanded and non-controlled small variations of the factors and also by the action of other random variables (Fig. 5.1). Consequently, when the experiments are planned so as to identify coefficients Po pj etc, they will apparently show different collected data. So, each experiment will have its own Pq P etc. coefficients. In other words, each coefficient is a characteristic random variable, which is observable by its mean value and dispersion. [Pg.328]

The examples where a CFE 2 plan has been divided into two or four blocks are not explicit enough to develop the idea that the relations of the unification of blocks are selected randomly. In the next example, a CFE 2 plan is developed with the purpose being to show the procedures to select the unification relations of inter-blocks. In this plan, the actions showing a systematic influence will be divided into two blocks or into four blocks with, respectively, eight experiments or four experiments per block. We start this new analysis by building the CFE 2 plan. Table 5.64 contains this CFE 2 plan and also gives the division of the two blocks when we use the ABCD interaction as a unification relation. [Pg.444]

The inlet gas composition was changed in accordance with an extended 2 factorial-designed experiment [10], For each temperature, the experiment was divided into two parts to avoid very long experiments with severe deactivation. Reference conditions were repeated three times during each run. The total experimental plan contained six runs, each with 10 experimental points. The order of the points and the length between the steps (143 - 176 min) were randomized. The experiments conducted at 780 K will be named A1 and A2, while those performed at 800 and 820 K will be called Bl, B2, Cl and C2. [Pg.674]

It is evident that experunents run at random also will give results at random. It is necessary to use planned experiments. It is, however, of tremendous importance how the experiments are planned and executed. There are no computational methods, no statistical tricks available which can extract the desired chemical information from experimental data, if the experiments have been run in such a way that there is no such information in the data. [Pg.19]

In the second type, the value of the independent variable alternates randomly. Such a plan of experiment is usually called a randomized plan. [Pg.260]

The randomized plan is also suited to many sensor experiments. Its main arguments are based on the fact that the external (conbolling) conditions of experiment can vary in time and some undetected faults can influence the value of the independent measuring variable. The main concept of randomization is based on the fact that the systematic influential factors, which are hard to control with certain accuracy, should become the accidental factors for their statistical control. However, the randomization may be unnecessary in the complex experiments, when the establishment of the fixed experimental conditions requires substantial extra time and the accidental sequence of transfer from one test condition to others brings even more time expenditures. [Pg.260]

Once a probable design has been selected, preliminary experiments can be taken from this, either chosen at random or by taking especially interesting or potentially difficult runs. Thus, they may be incorporated in the plan - when and if it is completed. [Pg.31]

O.IM bile salt (Xi = 0) and an equimolar lecithin to bile salt ratio X = 0). Also each distinct experiment was done twice. These replications, which are complete and carried out under identical experimental conditions, allow us to estimate the repeatability, without any external influence, and thus to have a good idea of the dispersion of the results and the extent of the experimental error. The 10 experiments are carried out in random order. The experiment design, plan, and the response data are all listed in table 4.2 in the standard order. [Pg.167]

When the residuals are plotted in the order in which the experiments were carried out, they should be scattered evenly about zero. However, there may be a slope demonstrating a trend in an uncontrolled factor that is affecting the results of the experiment. Provided the plan has been randomized, this will affect the estimations... [Pg.311]


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See also in sourсe #XX -- [ Pg.260 ]




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