Excel experimental design

The above experimental design constitute an excellent set of "preliminary experiments" for nonlinear models with several unknown parameters. Based on the analysis of these experiments we obtain estimates of the unknown parameters that we can use to design subsequent experiments in a rational manner taking advantage of all information gathered up to that point. 

To make cut pile carpets, two strands of BCF yarns are twisted together and heat-set with steam using a Superba heat setting machine at 135-145 °C or at 175-195 °C when heat-set with super-heated steam in a Suessen. An experimental design experiment [94] showed the higher the heat set temperature, then the lower is the bulk of the final carpet, but there is an increase in the tip definition and walk performance. The tufted carpets are then dyed with disperse dyes at atmospheric boil [95] in a continuous or a batch process. PTT carpets showed excellent resiliency in walk test experiments, equivalent to a nylon and much better than both PET and polypropylene, had lower static charge of <3.5 kV, and were resistant to coffee, mustard, betadine, red acid dyes and other stains [96],... 

As described in Section 7.4.2, one of the challenges of online LC-NMR is the need to match the chromatographic peak to the active volume of the CapNMR flow cell. An excellent discussion of the comparison of CapLC-NMR with other NMR probe types has been provided by Lewis et al. [17] Table 7.1 shows the sensitivity comparison of the CapNMR probe with larger volume probes. It is important to note that the experimental design used by these authors adjusted the concentration of analyte such... 

Optimization of a process or catalyst by experimental design such as two-factorial design can lead to significant reduction in time required to achieve the goal. In their excellent work, Mylroie et al. (3) reduced the time required for the optimization of the reductive alkylation process conditions by a factor of 10. Here, we turn our attention to the optimization of the catalyst rather than the process. 

An excellent exposition of split-plot experimental designs can be found in D.R. Cox s book, Planning of Experiments [42]. He states that split-plot designs are particularly useful when one (or more) factors are what he calls classification factors. These factors are included in the experiment to determine whether they modify the effect of the other factors or indicate how the other factors work. The classification factors are included to examine their possible interaction with the other factors. Lower precision is tolerated for comparisons of the classification factors, in order that the precision of the other factors and the interactions can be increased. In the standard terminology associated with split-plot experiments, the classification factors are called whole-plot factors and are applied to the larger experimental units. The smaller experimental units are called subplots. 

Figure 7-12 Spreadsheet for efficient experimental design uses Excel UNEST routine to fit the function y = mAxA + nv% + /Tfcxfc to experimental data by a least-squares procedure.

The European science community of the 1800s viewed most American scientists as inventors—clever, but not profound in their thinking or discoveries. This attitude began to change at the turn of the 20th century, principally because of the work of American scientists such as Robert Millikan, who excelled in his experimental designs and conclusions. In addition to research, he also spent much time preparing textbooks so that his students did not have to rely so much on lectures. He won a Nobel prize in 1923 and served as the president of Caltech from 1921 to 1945. 

An excellent review on experimental design which is followed by a valuable discussion of numerous scientific and educational aspects is given by STEINBERG and HUNTER [1984], In analytical chemistry experimental design has been used to optimize almost all types of analytical procedure because of its ease of use. 

In summary, the experimental design shows that (1) the samples selected were highly different, (2) temperature control is very important for precise measurement, and (3) there appears to be some operator effect in the determination of polydispersity. There are no interaction effects among operators, DCP instruments, and methods. For particle size measurement, however, different types of samples respond differently to the other factors in the experiment. In spite of this, the overall precision of the measurements by both the BLS method and the EGM is excellent. 

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. 

An excellent introduction to experimental design has been given by Box, Hunter and Hunter [5]. A general treatment is found in the book by Cochran dan Cox [10]. Many introductory text-books have appeared in recent years, some examples of which are given in the reference list [11],... 

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