• 한국의류학회지
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• 제35권11호
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• pp.1322-1332
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• 2011

This study investigates the influence of social desirability to questionnaire response and data analysis in order to identify the need for social desirability control in clothing consumer research. A questionnaire measuring social desirability, social face sensitivity, clothing shopping behavior, and demographic characteristics was developed. Responses of 234 respondents were analyzed using factor analysis, simple regression analysis, hierarchical regression analysis, descriptive analysis, and Cronbach's alpha analysis. The results were as follow. First, respondents were influenced by social desirability when they responded to items measuring other-conscious social face. Second, the result of regression analysis (that the independent variable was social formality) was less influenced by social desirability control because the influence of social desirability to social formality was insignificant. Conversely, the result of regression analysis (that the independent variable was other-conscious social face) was more influenced by social desirability control because the influence of social desirability to other-conscious social face was significant. This study is an initial study that notices the need for social desirability control in clothing consumer research.

• 한국지능시스템학회논문지
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• 제25권5호
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• pp.489-494
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• 2015

본 연구의 목적은 프로농구 경기의 승부 결과를 회귀모형을 이용하여 분석하는 것이다. 이를 위해 본 연구에서는 전통적인 회귀분석 방법과 문자적인 변수를 사용하는 퍼지회귀모형을 사용하였다. 승부의 결과를 두 팀 간의 점수차로 표현하여 분석한 일반회귀분석 방법에서는 두 팀의 점수차에 영향을 미치는 변수를 찾아 승부의 결과에 대한 회귀모형을 제시하였다. 그리고 두 팀의 승부 결과를 "대승, 승리, 신승, 석패, 패배 그리고 대패"와 같이 문자적으로 표현한 퍼지회귀모형에서는 각 팀의 경기력과 조직력을 퍼지수로 표현하여 각 팀의 경기력과 조직력이 승부의 결과에 미치는 영향을 분석하였다. 본 연구는 한국프로농구연맹(KBL, Korea Basketball League)에서 제공하는 2013~2014시즌의 자료와 프로농구의 결과를 분석하는 칼럼들을 이용하여 분석하였다.

• 소성∙가공
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• 제20권2호
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• pp.124-131
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• 2011

A flexible stretch forming process is useful for small quantity batch production because various shape changes of the flexible die can be achieved conveniently. In this study, the design variables, namely, the punch size, curvature radius and elastic pad thickness, were quantitatively evaluated to understand their influence on sheet formability using statistical methods such as the correlation and regression analyses. Forming simulations were designed and conducted by a three-way factorial design to obtain numerical values of a shape error. Linear relationships between the design variables and the shape error resulted from the Pearson correlation analysis. Subsequently, a regression analysis was also conducted between the design variables and the shape error. A regression equation was derived and used in the flexible die design stage to estimate the shape error.

• 한국항해항만학회지
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• 제34권7호
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• pp.559-566
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• 2010

The container port industry has been variously studied by many researchers, because the contemporary container transportation and container port industries play a pivotal role in globalization of the world economy. For container terminals, the productivity, affected by many factors, is an important target in measuring container terminal performance. Under this background, finding the critical factors affecting the productivity is necessary. Regression analysis can be used to identify which independent variables are related to the dependent variable, and explore the relationships of them. The aim of paper is to evaluate the factors affecting the productivity of Chinese major terminals by using a regression statistical analysis modeling approach, which is to establish the variable preprocessing model (VPM) and regression analysis model (RAM), by means of collecting the major Chinese container terminals data in the year of 2008.

• 한국환경과학회지
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• 제24권11호
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• pp.1443-1450
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• 2015

Wastewater treatment plant(WWTP) has been recognized as a high energy consuming plant. Usually many WWTPs has been operated in the excessive operation conditions in order to maintain stable wastewater treatment. The energy required at WWTPs consists of various subparts such as pumping, aeration, and office maintenance. For management of energy comes from process operation, it can be useful to operators to provide some information about energy variations according to the adjustment of operational variables. In this study, multiple regression analysis was used to establish an energy estimation model. The independent variables for estimation energy were selected among operational variables. The $R^2$ value in the regression analysis appeared 0.68, and performance of the electric power prediction model had less than ${\pm}5%$ error.

• 한국정밀공학회지
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• 제21권10호
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• pp.20-25
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• 2004

Using the multiple regression analysis cutting forces of turning processes have been predicted based on the cutting conditions such as feed rate(f), depth of cut(d), and cutting velocity(v). The statistical inference of the equation was checked by ANOVA test. The validity of the proposed regression analysis was verified by two sets of cutting tests of 27 cutting conditions and the additional cutting tests of 18 cutting conditions. From the results of analytical and experimental studies, it was found that there was no significant difference between the measured and predicted cutting forces. Also, the shear and friction characteristics of turning processes were analyzed with predicted cutting forces.

• 한국기계가공학회지
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• 제3권4호
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• pp.37-42
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• 2004

End-milling have been widely used in aircraft, automobile part and moulding industry. However, various working factors such as spindle speed, feed rate and depth of cut in end-milling have an effect on spindle vibration. There it is demanded the quantitative analysis of spindle vibration in order to get the optimum surface roughness. This study was carried out to analyze an influence of working factors on spindle vibration by design of Experiment. The results are shown that mathematical model of regression equation for an influence of working factors on vibration acceleration of spindle in end-milling by regression analysis is presented.

• 한국환경보건학회지
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• 제35권3호
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• pp.191-200
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• 2009

We investigated a trait of odor and the relationship between odor unit and odorous compounds using multiple regression analysis based on data compiled from Sihwa (SIC), Banwol (BIC), Banwol plating (BPIC) and Poseung industrial complex (PIC). These areas are odor control areas in Gyeonggi province. It was revealed that $NH_3$ and styrene concentrations in SIC and BPIC were relatively higher and $H_2S$ concentration especially in mc was more than five times higher than other areas. As a result of regression analysis using SAS, intensity of odor unit was highly related to concentrations of $H_2S$, TMA, styrene and n-valeraldehyde in SIC, $H_2S$, acetaldehyde, and butyraldehyde in BPIC and $NH_3$ in BIC.

• 한국안전학회지
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• 제15권3호
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• pp.1-6
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• 2000

In fatigue crack growth test, it is important not only to analyze characteristics of fatigue crack growth but also to determine the threshold stress intensity factor, ${\Delta}K_{th}$. which is the threshold value of fatigue crack growth. Linear regression analysis using fatigue test data near the threshold is suggested to determine the ${\Delta}K_{th}$ in the standard test method but the ${\Delta}K_{th}$ can be affected by a fitting method. And there are some limitations on the linear regression analysis in the case of small number of test data near the threshold. The objective of this study is to investigate differences of the ${\Delta}K_{th}$ due to regression analysis method and to evaluate the relative error range of the ${\Delta}K_{th}$ in same fatigue crack growth test data.

• Communications for Statistical Applications and Methods
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• 제29권4호
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• pp.453-469
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• 2022

The study of immune cellular composition has been of great scientific interest in immunology because of the generation of multiple large-scale data. From the statistical point of view, such immune cellular data should be treated as compositional. In compositional data, each element is positive, and all the elements sum to a constant, which can be set to one in general. Standard statistical methods are not directly applicable for the analysis of compositional data because they do not appropriately handle correlations between the compositional elements. In this paper, we review statistical methods for compositional data analysis and illustrate them in the context of immunology. Specifically, we focus on regression analyses using log-ratio transformations and the alternative approach using Dirichlet regression analysis, discuss their theoretical foundations, and illustrate their applications with immune cellular fraction data generated from colorectal cancer patients.