• The Korean Journal of Applied Statistics
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• v.22 no.2
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• pp.435-442
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• 2009

Multiple genes interacting is a difficult due to the limitations of parametric statistical method like as logistic regression for detection of gene effects that are dependent solely on interactions with other genes and with environmental exposures. Multifactor dimensionality reduction(MDR) statistical method by dummy variables was applied to identify interaction effects of single nucleotide polymorphisms(SNPs) responsible for longissimus mulcle dorsi area(LMA), carcass cold weight(CWT) and average daily gain(ADG) in a Hanwoo beef cattle population.

• Korean Journal of Human Ecology
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• v.15 no.4
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• pp.623-630
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• 2006

The purpose of this study is to do research hairdressers' knowledge of hairless head dummy's brand name, and to suggest and develop various hairless head dummy for the students who are learning hair styling in the colleges and the academies, for the hairdressers working in the beauty salons. Using only one and same kind of hairless head model is not appropriate for hairdressers and students being trained hair styling skill, because people have a variety of head shapes. Three hundred twenty nine persons who live in Iksan area are selected as subjects. The results of the study are as follow: by the analysis of subjects' knowledge of hairless head dummy's brand name, most of them didn't know it exactly. This study deduced that there is a significant relation between the utility of hairless head dummy and subjects' intention of purchasing the dummy. To put it in detail, in case of college students, there is little significant difference between them. But in case of academy students, there is. By the regression analysis, especially, in case of hairdressers working in beauty salons and academy students, four conditions did significantly matter in their purchasing the dummy: first, whether the respondents owns it, second, whether it is helpful to themselves, third, whether they have ever used foreign products and, finally, whether they have intention to purchase various hairless head dummys or not. In conclusion, it depended on each group position whether their knowledge of brand names of hairless head model affects their purchase of the dummy or not.

• Journal of Korean Society for Quality Management
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• v.29 no.3
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• pp.124-137
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• 2001

In general, it is very efficient and effective to use screening variables that are correlated with the performance variable in case that measuring the performance variable is impossible (destructive) or expensive. The general methodology for searching surrogate variables is regression analysis. This paper considers the inspection problem in CRT (Cathode Ray Tube) production line, in which the performance variable (dependent variable) is binary type and screening variables are continuous. The general regression with dummy variable, discriminant analysis and binary logistic regression are considered. The cost model is also formulated to determine economically inspection procedure with screening variables.

• New & Renewable Energy
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• v.10 no.3
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• pp.6-13
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• 2014

This paper presents a computational study of thermal performance and construction cost of horizontal ground heat exchangers (GHEs). GLD (ground loop design) simulations of various type of GHEs were carried out. Construction costs were also calculated based on standard estimating, and compared with vertical type GHE system. Besides that, dummy regression analysis was conducted to study the influence of design parameters on the simulation results in horizontal ground heat exchanger system.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.37-46
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• 2023

The main aim of the article is to solve the problem of automating price monitoring using marketing forecasting methods and Excel functionality under martial law. The study used the method of algorithms, trend analysis, correlation and regression analysis, ANOVA, extrapolation, index method, etc. The importance of monitoring consumer price developments in market pricing at the macro and micro levels is proved. The introduction of a Dummy variable to account for the influence of martial law in market pricing is proposed, both in linear multiple regression modelling and in forecasting the components of the Consumer Price Index. Experimentally, the high reliability of forecasting based on a five-factor linear regression model with a Dummy variable was proved in comparison with a linear trend equation and a four-factor linear regression model. Pessimistic, realistic and optimistic scenarios were developed for forecasting the Consumer Price Index for the situation of the end of the Russian-Ukrainian war until the end of 2023 and separately until the end of 2024.

• Korea Journal of Hospital Management
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• v.13 no.4
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• pp.1-26
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• 2008

This study examines the statistical relationship between medical specialists and managerial performance, using regression analysis with the number of medical specialists per 100 beds as the independent variable and the managerial performance index as the dependent variable. Managerial performance index incorporated the number of out-patients per specialist, the number of in-patients per specialist, the volume of revenue per specialist, the number of beds per specialist, and the average length of stay. To compare different groups of hospitals, dummy variable was applied to five groups of hospitals according to size: 100-299 beds, 300-599 beds, 600-899 beds, 900-1199 beds, and more than 1200 beds. The data consisted of 181 general hospitals with more than 100 beds, which included 28 public hospitals, 73 corporate hospitals, 64 university hospitals and 16 private hospitals. Of those, 87 hospitals were located in big cities and 94 hospitals in medium to small cities. This study used hospitals from the Korean Hospital Association, and data published in 2004. The collected data sample was analyzed using the SPSSWIN 12.0 version, and the study hypothesis was tested using regression analysis. The findings of this study are summarized as follows: Hypothesis 1 predicting a negative effect of the number of medical specialists on the number of out-patients per specialist was supported with statistical significance. The analysis of dummy variable showed causality in all the hospital groups larger than the group of 100-299 beds. Hypothesis 2 predicting a negative effect of the number of medical specialists on the number of in-patients per specialist was supported with statistical significance. The analysis of dummy variable showed causality in the hospital group of 300-599 beds when compared to the group of 100-299 beds. Hypothesis 3 predicting a negative effect of the number of medical specialists on the volume of revenue per specialist was not supported. However, the analysis of dummy variable showed that the volume of revenue per specialist increased in the hospital groups of 600-899 beds, 900-1199 beds, and over 1200 beds, when compared to the group of 100-299 beds. Hypothesis 4 predicting a negative effect of the number of medical specialists on the average length of stay was supported with statistical significance. The analysis of dummy variable showed causality in the hospital group of 300-599 beds, when compared to the group of 100-299 beds. Results of this study show that the number of the medical specialists per 100 beds is an important factor in hospital managerial performance. Most hospitals have tried to retain as many medical specialists as possible to keep the number of patients stable, to ensure adequate revenue, and to maintain efficient managerial performance. Especially, the big hospitals with greater number of beds and medical specialists have shown greater revenue per medical specialist despite the smaller number of patients per medical specialist. Findings of this study explains why hospitals in Korea are getting bigger.

• International Journal of Advanced Culture Technology
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• v.6 no.3
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• pp.12-21
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• 2018

This study was a cross-sectional survey of the effects of pregnancy necessity recognition on emotional happiness and mediation effect of health control behavior on it. A total of 200 participants in the study were collected from structured questionnaire online and the data collection was from July $1^{st}$ to July $31^{st}$, 2018. Health control behavior questionnaire was developed by Wallston, K.A., Wallston, B.S. & Devellis, R (1978), Emotional happiness was analyzed by using PANAS (positive and negative affect schedule) developed by Watson, Clark and Tellegen (1988). The collected data were chai-square($X^2$), Pearson correlation, Dummy regression analysis, simple regression analysis, and the mediated effect analysis by SPSS 18.0. As a result, Under statistical significance, there were differences in the recognition of pregnancy necessity were depending on religion, participant's age, number of siblings, thought of optimal marriage age(p<0.05). More siblings, more religious, older age, and more recognized the pregnancy necessity. The analysis of Pearson correlation with the pregnancy necessity, health control behavior, and emotional happiness reveled that it was relevant (p<0.01). Dummy regression analysis showed that people who thought that pregnancy was necessary were 0.700 times more likely to felt emotional happiness that people who thought it was unnecessary (p<0.01). Analysis on the mediation of health control behavior, in which the effects of pregnancy recognition on emotional happiness, showed that it was effect (other people's health control behavior: B:.299, p<0.01, internal health control behavior : B:.217, p<0.05). Based on these results, this study suggested that to promote pregnancy recognition, families with brother and sister should be programmed with recommendations for exercise and alcohol abstinence, religious belief and health control programs.

• Korean Journal of Construction Engineering and Management
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• v.13 no.2
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• pp.91-101
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• 2012

In planning phase of Public Multi-Housing Projects, it is required to develop the methodology and criteria for fair cost prediction with influencing power from planning phase to occupancy phase. Many studies still have focused on the prediction of cost by multiple regression. However, there is no logical explanation about the influence of nonmetric variables for the prediction of cost in planning phase. Accordingly, this research pursues a cost prediction model including nonmetric variables for use in planning phase. There are 3 steps of this research : 1) Finding the factors influencing construction cost and assigning variables for a multiple regression. 2) Conducting a dummy regression analysis with nonmetric variables and model validation by comparing actual cost data. 3) Developing the ratio of RC structure cost to wall structure cost by using cost predection model. The results could establish cost prediction process including the influence of nonmetric variables and the ratio of RC structure cost to wall structure cost.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.05a
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• pp.234-239
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• 2002

한국인 인체모델은 동적 환경에서 정면 및 측면 충돌에 대한 지체의 가속도를 얻을 수 있도록 개발되었다. 우선 GEBOD에 입력하기 위한 32개의 한국인 인체치수를 선별하고, 15개의 지체를 가진 한국인 인체모델을 구성한다. 손 동작의 감성평가에 이용하기 위해 손을 독립된 지체로 분리한 17개 지체의 인체모델을 완성한다. MADYMO를 통한 정면충돌 테스트에서는 Hybrid III에 비해 한국인의 머리와 흉부 가속도가 비교적 높게 나왔고, 측면충돌 테스트에서 흉추 1번의 가속도는 ISO에서 요구하는 범위의 상한값을 조금 벗어나는 결과를 얻었다.

• Asian Journal of Innovation and Policy
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• v.12 no.1
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• pp.101-130
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• 2023

The increasing cost, and demand for, household energy has increased attention to the phenomena of energy burdens. Despite this increased attention, a lack of consensus remains in pinpointing the strongest predictors, and geographic differences, that exist within the energy ecosystem. This study addresses this gap by utilizing a series of dummy variable regressions across cities, suburbs, and rural areas within Erie County, New York-a county noted to have particularly high energy burdens. Specifically, three types of predictor sets were incorporated into the methodology: a set of socioeconomic variables, physical variables, and a combination of both variable sets. The results of this study suggest that cities tend to have the highest electricity burdens. Despite the aging infrastructure in Erie County, high energy burdens were driven primarily by socioeconomic factors such as housing cost burden and poverty status. Lastly, this study explores various planning and policy implications Erie County can utilize to reduce energy burdens. In turn, this study highlights the importance of focusing policy efforts on existing social service programs to provide support to the region's neediest households.