Experimental design and data

Each observation in any branch of scientific investigation is inaccurate to some degree. Often the accurate value for the concentration of some particular constituent in the analyte cannot be determined. However, it is reasonable to assume the accurate value exists, and it is important to estimate the limits between which this value lies. It must be understood that the statistical approach is concerned with the appraisal of experimental design and data. Statistical techniques can neither detect nor evaluate constant errors (bias) the detection and elimination of inaccuracy are analytical problems. Nevertheless, statistical techniques can assist considerably in determining whether or not inaccuracies exist and in indicating when procedural modifications have reduced them. 

The saturated fractional factorial designs are satisfactory for exactly 3, or 7, or 15, or 31, or 63, or 127 factors, but if the number of factors is different from these, so-called dummy factors can be added to bring the number of factors up to the next largest saturated fractional factorial design. A dummy factor doesn t really exist, but the experimental design and data treatment are allowed to think it exists. At the end of the data treatment, dummy factors should have very small factor effects that express the noise in the data. If the dummy factors have big effects, it usually indicates that the assumption of first-order behavior without interactions or curvature was wrong that is, there is significant lack of fit. 

Bourquin J., Schmidli, H., Van Hoogevest, R, and Leuenberger, H., Comparison of ANN with classical modeling techniques using different experimental designs and data from a galenical study on a solid dosage form, Eur. J. Pharm. Sci., 6, 287-301 (1998). 

The study of repetitive sequences utilizes many relatively routine techniques in molecular genetics that are described in a number of excellent manuals3445 and are not discussed here. Instead, we consider the aspects of experimental design and data analysis that are specific for the study of repeated DNA families. 

OPTIMISATION OF THE COMPOSITION OF FERROMAGNETIC BLENDS USING A FLOW CHART FOR EXPERIMENTAL DESIGN AND DATA MANAGEMENT Orlic R... 

Ruggedness/robustness Defined based on an experimental design and data (sensitive parameters and a range for each parameter in the final test method)... 

Joachim J, Kalantzis G, Joachim G, et al. Pregelatinized starches in wet granulation experimental design and data analysis. Part 2. Case of tablets. SEP Pharma Sci 1994 4(6) 482- 86. 

In contrast, in tighter epithelia such as Caco-2 and in artificial membranes such as HDM, the permeability of the ionized forms of the drugs and the paracellular permeability are lower or insignificant, respectively. These findings will have implications in the experimental design and data interpretation of pH-dependent drug transport experiments in cell culture models as well as in artificial membrane models, such as HDM and PAMPA. 

Fortunately, various chemometric-based techniques, including multivariate experimental design and data analysis techniques, have been devised to aid in optimizing the performance of systems and extend their separation capabilities. In broadest terms, chemometrics is a subdiscipline of analytical chemistry that uses mathematical, statistical, and formal logic to (10) ... 

Because the disposal of retorted shale is, ultimately, a field exercise, this paper will discuss the experimental design and data from field studies which have been carried out. Laboratory experimentation and data will be used to complement the results of field studies. Two field studies, compaction and permeability, were carried out during the Paraho research operations. 

Statistics does not perform miracles and in no way can substitute specialized technical knowledge. What we hope to demonstrate is that a professional who combines knowledge of statistical experimental design and data analysis with sohd technical and scientific training in his own area of interest will become more competent, and therefore even more competitive. 

We are chemists, not statisticians, and perhaps tbis differentiates our book from most others with similar content. Although we do not believe it is possible to learn the techniques of experimental design and data analysis without some knowledge of basic statistics, in this book we try to keep its discussion at the minimum necessary — and soon go on to what... 

Experimental Design and Data Analysis With such lengthy... 

H. Zhang, M.O. Balaban, J.C. Prindpe, K. Portier, Quantification of spice mixture compositions by electronic nose part I. Experimental design and data analysis using neural networks. J. Food Sd. E Eood Eng. Phys. Prop. 70, E253-258 (2005)... 

Various techniques have been routinely used to provide evidence for GPCR dimerization. However, each of these methodologies has its caveats, which should be considered for optimal experimental design and data interpretation. In fact, one definitive approach does currently not exist, and consequently multiple approaches... 

Because there are so many geometries of adhesive joints encountered, and so many types of stress applied (tension, shear, torsion, thermal, etc.), the analysis of a given system must be tailored to meet the specific application. The processes of experimental design and data analysis, therefore, become quite complicated. It should also be kept in mind that flaws such as those often implicated in adhesive failure can also lead to apparent cohesive failure in the bulk material. 

The Practice of Dynamic Combinatorial Libraries Analytical Chemistry, Experimental Design, and Data Analysis... 

The normal distribution has the familiar symmetrical beU shape as shown in Fig. 1 and is the basis for the most common statistical techniques of experimental design and data analysis. The characteristics of this distribution are described in the section on Terminology. Mass loss, mass gain, thickness loss, corrosion potential, corrosion rate, and pitting area may have a normal distribution. Although this may not be an established fact, in the past many researchers have assumed normal distributions for such data with apparent success. 

Corrosion researchers can gain a greater degree of confidence in their experimental results if they have a basic understanding and use statistical techniques of experimental design and data analysis. Statisticians cannot property design... 

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