• Communications for Statistical Applications and Methods
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• v.9 no.3
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• pp.743-752
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• 2002

The estimation of the response curve is the important problem in the quantal bioassay. When we estimate the response curve, we determine the design points in advance of the experiment. Then naturally we have a question of which design would be optimal. As a response curve estimator, locally weighted quasi-likelihood estimator has several more appealing features than the traditional nonparametric estimators. The optimal design density for the locally weighted quasi-likelihood estimator is derived and its ability both in theoretical and in empirical point of view are investigated.

• Journal of the Korea institute for structural maintenance and inspection
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• v.25 no.6
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• pp.235-244
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• 2021

This study analyzes the applicability of limit state design method on bridge evaluation by considering the experiment of the existing bridge. The test strength of the member is obtained from the PSC beam bridge experiment. The test strength is compared with the calculated strength obtained from the statistical characteristics of material test strength and the two values are almost the same. The response modification factor and dynamic impact factor are obtained from the vehicle loading test. The rating factor is calculated by applying limit state design method as well as current evaluation method and the results are compared. The reliability index of the test bridge is calculated by using the statistical properties of the member strength obtained from material test and simulation. When the statistical properties of the PSC beam tested in this study are applied, the reliability index with a larger value was obtained than the reliability index obtained with the statistical properties of the design code.

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.9
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• pp.1381-1386
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• 2018

Animal experiments are essential to the study of animal nutrition. Because of the large variations among individual animals and ethical and economic constraints, experimental designs and statistical analyses are particularly important in animal experiments. To increase the scientific validity of the results and maximize the knowledge gained from animal experiments, each experiment should be appropriately designed, and the observations need to be correctly analyzed and transparently reported. There are many experimental designs and statistical methods. This editorial does not aim to review and present particular experimental designs and statistical methods. Instead, we discuss some essential elements when designing an animal experiment and conducting statistical analyses in animal nutritional studies and provide guidelines for submitting a manuscript to the Asian-Australasian Journal of Animal Sciences for consideration for publication.

• Korean Chemical Engineering Research
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• v.46 no.4
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• pp.756-763
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• 2008

The aim of this work was to obtain uniform and well-dispersed spherical silver nanoparticles using statistical design-of-experiment methods. We performed the experiments using 2 k fractional factorial designs with respect to key factors of a general chemical reduction method. The nanoparticles prepared were characterized by SEM, TEM and UV-visible absorbance for particle size, distribution, aggregation and anisotropy. The data obtained were analyzed and optimized using a statistical software, Minitab. The design-of-experiment methods using quantified data enabled us to determine key factors and appreciate interactions between factors. The measured properties of nanoparticles were dominated not only by individual one or two main factors but also by interactions between factors. The appropriate combination of the factors produced small, narrow-distributed and non-aggregated silver nanoparticles of about 30 nm with approximately 10% standard deviation.

• The Korean Journal of Applied Statistics
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• v.10 no.1
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• pp.29-36
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• 1997

Four statistical packages useful for statistical process control are reviewed. MINITAB, RS, SAS, and SPSS are compared in terms of general capability, control chart, process capability, design of experiment and Taguchi method.

• 대한공업교육학회지
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• v.30 no.1
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• pp.56-67
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• 2005

The purpose of this study was to examine the effects of analytic rubrics on learners' self-directed learning ability in information technology unit assessment. The experiment and control groups were 4 classes of the 2nd grade in B middle school located in Daejeon. The pretest was performed to check the group homogeneity. For the experiment design, the nonequivalent control group design as a type of quasi-experimental design was used. The experiment was composed of 5 sessions. Statistical significance was p < .05 to verify the hypothesis, and SPSS 12.0 for Windows was used for statistical treatment. The results from this study were as follows: (1) The application of analytic rubrics in information technology unit assessment affected learners' self-directed learning ability in a positive way in 4 factor's(openness, self-concept, intrinsic motivation, self-evaluation) but does not affected in 3 factor's(autonomy, creativity, problem solving). (2) The difference in sex was not a statistically significant factor in the application of analytic rubrics in information technology unit assessment. Based on the results of the experiment, two suggestions were made to promote the application of rubrics in technology education assessment. (1) Research and development of many types of rubrics for technology education are needed. (2) Systematic training of rubrics for technology teachers is needed.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.347-349
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• 2014

Model verification and validation (V&V) is a current research topic to build computational models with high predictive capability by addressing the general concepts, processes and statistical techniques. The hypothesis test for validity check is one of the model validation techniques and gives a guideline to evaluate the validity of a computational model when limited experimental data only exist due to restricted test resources (e.g., time and budget). The hypothesis test for validity check mainly employ Type I error, the risk of rejecting the valid computational model, for the validity evaluation since quantification of Type II error is not feasible for model validation. However, Type II error, the risk of accepting invalid computational model, should be importantly considered for an engineered products having high risk on predicted results. This paper proposes a technique named as the response-adaptive experimental design to reduce Type II error by adaptively designing experimental conditions for the validation experiment. A tire tread block problem and a numerical example are employed to show the effectiveness of the response-adaptive experimental design for the validity evaluation.

• The Korean Journal of Applied Statistics
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• v.27 no.6
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• pp.1029-1038
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• 2014

Bayesian experimental design is a useful concept in applied statistics for the design of efficient experiments especially if prior knowledge in the experiment is available. However, a theoretical or numerical approach is not simple to implement. We review the concept of a Bayesian experiment approach for linear and nonlinear statistical models. We investigate relationships between prior knowledge and optimal design to identify Bayesian experimental design process characteristics. A balanced design is important if we do not have prior knowledge; however, prior knowledge is important in design and expert opinions should reflect an efficient analysis. Care should be taken if we set a small sample size with a vague improper prior since both Bayesian design and non-Bayesian design provide incorrect solutions.

• The Korean Journal of Applied Statistics
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• v.17 no.3
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• pp.419-430
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• 2004

Since cDNA microarray experiments can monitor expression levels for thousands of genes simultaneously, the experimental designs and their analyzing methods are very important for successful analysis of microarray data. The loop design is discussed for selecting differentially expressed genes among several treatments and the analysis of variance method is introduced to normalize microarray data and provide estimates of the interesting quantities. MA-ANOVA is used to illustrate this method on a recently collected loop designed microarray data at Cancer Metastasis Research Center, Yonsei University.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.35-40
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• 2006

For the maritime traffic safety assessment of vessels navigating in harbor or fairway, simulation techniques by using shiphandling simulator system have been traditionally used. When designing the simulation experiments and when analyzing the simulation results, however, there has been a little systematic method. Ship-handling simulations can be regarded as a kind of statistical experiment by using ship-handling simulator system, which means that shiphandling simulation conditions should be designed statistically and that the simulation results should be statistically analyzed as well. For the safe and economic design of harbor and fairway, reasonable decisions based upon the scientific analysis of shiphandling simulation results are indispensable. In this paper, various statistical methods, such as Bayes theorem, statistical hypothesis testing, and probability distributions, are reviewed with a view to application to maritime traffic safety assessment. It is expected that more reasonable decisions on harbor and fairway design can be made from shiphandlers' view point by using statistical methods.