Results 221 to 230 of about 15,863 (273)

Algebraic statistics of level codings for fractional factorial designs

Journal of Statistical Planning and Inference, 2008
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
G. PISTONE, ROGANTIN, MARIA PIERA
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Some experiences teaching factorial design in introductory statistics courses

Journal of Applied Statistics, 1987
A major challenge in teaching statistics is to convey how statistics is used in solving real problems. Introductory courses often fail to provide students with a sense of how to apply statistical ideas. This paper will describe our experiences with a teaching approach in which students generate and analyse their own data by conducting a factorial ...
Ron S. Kenett, David M. Steinberg
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Rank statistics under dependent observations and applications to factorial designs

Journal of Statistical Planning and Inference, 1994
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Brunner, Edgar, Denker, Manfred
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Preparation and optimization of PIT solid lipid nanoparticles via statistical factorial design

European Journal of Medicinal Chemistry, 2012
The objective of this study was the preparation, physico-chemical characterization and statistical optimization of cationic solid lipid nanoparticles (SLN) prepared by the PIT method as potential carrier for gene therapy, emphasizing the application of factorial design in such a kind of studies.
CARBONE, CLAUDIA, TOMASELLO, BARBARA, Ruozi B, RENIS, Marcella, PUGLISI, Giovanni   +4 more
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Parametric statistics and levels of measurement: Factorial designs and multiple regression.

Psychological Bulletin, 1990
Let Y be a continuous, ordinal measure of a latent variable θ. In general, for factorial designs, an analysis of variance of the observed variable Y cannot be used to draw inferences about main effects and interactions on the latent variable θ even when the standard normality and equality of variance assumptions hold.
Mark L. Davison, Anu R. Sharma
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Statistical Analysis of Factorial Diallel Design over Environments

Biometrical Journal, 1987
AbstractStarting from the experimental situation that in each of a environments all mp combinations between m maternal and p paternal genotypes are raised in b replications (blocks), a linear model is formulated for a quantitative character. On the basis of this model formulae for the analysis of variance are given.
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A STATISTICAL ANALYSIS OF FRACTIONAL FACTORIAL DESIGN USING A FUZZY PROBABILISTIC APPROACH

2023
In factorial experiments, treatment combinations increase as the number of factors increases. While handling a large number of factors, many difficulties are encountered. Moreover, mechanical errors like mistaken identification of plots, wrong labeling of treatments, etc., may creep in.
Sri Devi, P., Pachamuthu, M.
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Sulfate removal from mine-impacted water by electrocoagulation: statistical study, factorial design, and kinetics

Environmental Science and Pollution Research, 2020
This work aimed to remove sulfate and acidity from mine-impacted water (MIW) via electrocoagulation (EC), a technique which stands as an advanced alternative to chemical coagulation in pollutant removal from wastewaters. The multiple electrochemical reactions occurring in the aluminum anode and the stainless steel cathode surfaces can form unstable ...
Caroline Rodrigues, Hioná V. Dal Magro Follmann, Dámaris Núñez-Gómez, Maria Eliza Nagel-Hassemer, Flávio R. Lapolli, María Ángeles Lobo-Recio   +5 more
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Statistical robust technique procedures for fractional factorial design with non constant variance

AIP Conference Proceedings, 2017
Fractional factorial design (FFD) has been widely used in engineering, agricultural, biology and social sciences. Although FFD is considered a conventional design, there still occurs a basic problem such as nonconstant variance may affect parameter estimation.
Nadia Mohd Yunus, Nora Muda
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Design and statistical analysis of confounded factorial experiments

2018
Ten confounded factorial experiments were designed with the purpose of filling in the existing gaps among the available plans. The method of analyzing such experiments was presented and illustrated by the 5 x 2 x 2 experiment. For each design, the reasons why a particular plan was adopted were discussed; the instructions for computing the sums of ...
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