• The Korean Journal of Applied Statistics
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• v.35 no.5
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• pp.579-591
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• 2022

Functional data is collected in various fields. It is often necessary to test whether there are differences among groups of functional data. In this case, it is not appropriate to explain using the point-wise ANOVA method, and we should present not the point-wise result but the integrated result. Various studies on functional data analysis of variance have been proposed, and recently implemented those methods in the package fdANOVA of R. In this paper, I first explain ANOVA and multivariate ANOVA, then I will introduce various methods of analysis of variance for univariate and multivariate functional data recently proposed. I also describe how to use the R package fdANOVA. This package is used to test equality of weekly temperatures in Seoul and Busan through univariate functional data ANOVA, and to test equality of multivariate functional data corresponding to handwritten images using multivariate function data ANOVA.

• The Korean Journal of Applied Statistics
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• v.15 no.2
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• pp.405-414
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• 2002

We consider the problem of estimating the error variance of in a two-way mixed-effects ANOVA model using noninformative priors. First, we derive Jeffreys' prior, a reference prior, and matching priors. We then provide marginal posterior distributions under those noninformative priors. Finally, we provide graphs of marginal posterior densities of the error variance and credible intervals for the error variance in two real data set and compare these credible intervals.

• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1409-1419
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• 2013

We analyzed the data from KYPS using the latent growth model which has been widely studied as an analysis method of longitudinal data. In this study, we applied repeated measures ANOVA to unconditional model in order for faster decision of the unconditional model of the latent growth model. Also, we compared the six-type models, the quadratic model and the model of which repeated measures ANOVA is applied.

• The Korean Journal of Applied Statistics
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• v.8 no.1
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• pp.75-87
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• 1995

Computer graphics approach is a powerful tool when we are to explore the effects of the change of a part of the data, or the effects of the alteration of the characteristics of the statistical model currently employed. The paper describes the methods to implement dynamic graphics for the process of analysis of variance, and the methods to graphically represent ANOVA type data. The paper the describes a dynamic graphics software developed by the author for two-way ANOVA model.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.11
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• pp.69-75
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• 2019

Oil seals have a great effect on transmission performance and durability. In this study, the optimal rubber mix was derived using dispersion analysis to obtain excellent oil-seal rubber properties. ANOVA was performed twice. The factors were polymers, carbon, magnesium oxide, and calcium hydroxide, which were used as four factors in ANOVA. The response factors were four items (hardness, tensile strength, elongation rate, and compression deformation) obtained through an experiment with a confidence level of 95%. In the first ANOVA, 168 tests were performed, and in the secondary ANOVA, 24 physical tests were conducted using polymers and carbon derived from the primary ANOVA. Through the ANOVA, we derived a rubber mixture recipe.

• The Journal of the Korea Contents Association
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• v.5 no.5
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• pp.266-272
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• 2005

This study is to empirically analyze the effects on job performance of Accounting Information Systems, Analysis methods were used to Cronbach's Alpha analysis, Factor analysis, analysis of variance(ANOVA) and regression in odor by the contingency grouping method. The results of this study are as follows : First, The regression analysis had effects on AIS utility and job performance. Second, The Analysis of variance(ANOVA) had non-effects on systems operating degree and systems satisfaction. Third, The input variables of information accuracy and systems satisfaction had additional effect about IT capability.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.11 no.5
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• pp.121-128
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• 2012

The optimization of cooling system parameters for designing injection mold is very important to acquire the highest part quality. In this paper, the integration of computer simulations of injection molding and Analysis of Variance(ANOVA) with orthogonal array was used as a design tool to optimize the cooling system parameters aimed at minimizing the part warpage. The design optimizer was applied to find the optimum levels of cooling system parameters for a dustpan. This optimization resulted in more uniform temperature distribution over the part and significant reduction of a part warpage, showing the capability of present method as an effective design tool. The whole optimization process was performed systematically in a proper number of cooling simulations. The design optimizer can be utilized effectively in the industry practice for designing mold cooling system with less cost and time.

• 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.

• The Korean Journal of Applied Statistics
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• v.26 no.6
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• pp.873-887
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• 2013

The axis of rotation in biomechanics is a major tool to investigate joint function; therefore, many methods to estimate the axis of rotation have been developed. However, there exist several problems to describe, estimate, and test the axis statistically. The axis is directional data(axial data) and it should not be analyzed with traditional statistics. A proper comparative method should be considered to compare axis estimating methods for the same given data ANOVA (analysis of variance) is a frequently used statistical method to compare treatment means in experimental designs. In case of the axial data response assumed to come from Watson distribution, there are a few ANOVA method options. This study constructed ANOVA models for within-subjects designs of axial data. Two models (one within-subjects factor and two within-subjects factors crossed design) were considered. The empirical data used in this study were instantaneous axes of rotation of flexion/extension at the knee joint and the flexion/extension and pronation/supination at the elbow joint. The results of this study can be further applied to the various analysis of experimental designs.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.6
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• pp.9-16
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• 2020

This study aims to assess the effects of specimen thickness (ST) on fatigue crack growth in the early stages of crack propagation and near failure in magnesium alloys. The analysis of variance (ANOVA) method was adopted because fatigue crack propagation in magnesium alloys exhibits statistical behavior. The equality of variance test and residual diagnostics were performed on the grown cracks to confirm the validity of ANOVA by verifying the normal distribution and mutual independence of the residuals and their homoscedasticity. ANOVA confirmed that ST heavily impacts crack growth; i.e., when ST is smaller, cracks grow faster in the early crack propagation stage and break more quickly before the formation of larger cracks. We found that ST significantly affects fatigue crack growth in the early crack propagation stage and near the failure stage in magnesium alloys. The regression model was also used to predict crack formation near the failure stage.