factorial experiment


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factorial experiment

an experiment in which all treatments are varied together rather than one at a time, so the effect of each or combinations of several can be isolated and measured.
References in periodicals archive ?
with the results from the factorial experiment, as will be discussed in
Summary of ANOVA for 2X 10 Factorial Experiments with repeated measures on the Second Factor (10 Times)
Table 3 shows the analysis of variance for the percentage of starch, where a factorial experiment is carried out under a completely randomized design.
In the first stage, the ANOVA was carried out by using the statistical tool Minitab 15 with the Taguchi method as the DOE, in order to screen out the IMPP having a great influence on the two objectives, and then significant IMPP were obtained for full factorial experiments. In the second stage, the M-SVR and BPNN models were built and then trained and tested according to the data from full factorial experiments, to obtain the mapping relationships between key IMPP and objectives.
The 2-level full factorial experiment is applied to divide risk factors into two parts: risk factors that have a significant impact on the financial and economical state of the observed enterprises and insignificant factors.
Let a triple factorial experiment conducted in CRD with factors [alpha], [beta] and [gamma] considered in a, b and c levels, respectively, replicated J times.
In this study, a 2 x 2 factorial experiment was designed to investigate the effects of dietary protein and carbohydrate level on the biochemical proximate composition of gonad tissue in Lytechinus variegatus (non-isocaloric; lipid content was held constant).
An experimental work should be conducted involving designing, preparing, and testing various trial mixtures according to the full factorial experiment design considering the various possible combinations of the levels of the mixture variables within their selected ranges of variation.
Along the calculated direction, the expected location of optimum point is predicted and the new cycle of factorial experiment and response surface estimation around the predicted point is performed (Mayers, Montgomery 2002; Levisauskas et al.
A factorial experiment (3 N levels x 3 K levels) in a Completely Randomized Design with four replications was used.
In a factorial experiment, the effects of a number of different factors can be studied at the same time.