• Proceedings of the Korean Society for Quality Management Conference
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• 2006.04a
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• pp.330-333
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• 2006

Many practical problems of quality control in service management are derived from the use of ordinal variables. Ordered linguistic variables differ from measurement variables. This paper presents a new control chart of a production process based on ordinal variables.

• Journal of the Korean Home Economics Association
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• v.40 no.7
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• pp.83-100
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• 2002

The purpose of this study is to examine related variables to goods purchase by consumers using the home shopping of cable TV. For the purpose accomplishment, this study analyzed the variables which influence on the purchase by demographic variables, consumers'shopping propensity, perceived risk and benefit. The major findings are as follows; In the purchase of convenience goods, the variables which influence positively are sex, job(housewife), instantly impulse purchasing propensity, and diversity of goods information. On the other hand, the variables which influence negatively are risk of delivery & returned goods, and risk of quality. In the purchase of shopping goods, the variables which influence positively are state of marriage, job(nonspecialist), and diversity of goods information. On the other hand, the variables which influence negatively are pleasure of shopping-oriented, risk of delivery & returned goods, and risk of quality. In the purchase of specialty goods, the variables which influence positively are sex, income, convenience of time, and convenience of approach. On the other hand, the variables which influence negatively are pleasure of shopping-oriented, and risk of price & information restriction.

• Korean Journal of Child Studies
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• v.27 no.6
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• pp.249-261
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• 2006

This study investigated the influence of socio-environmental variables and cognitive variables on adolescent depression. Subjects were 494 middle and high school students of Deagu. The instrument was a self-report questionnaire; data were analyzed by t-test, stepwise multiple regression and path analysis. Among Socio-environmental variables, social support variables had a stronger effect on depression than stress. Among cognitive variables, automatic thought had a stronger effect on depression than cognitive distortion and socio-environmental variables. In path analysis, social support had a direct effect on cognitive distortion and automatic thought. Automatic thought served as a mediater of the relation between social support and depression. Although adolescent stress resulted in high depression, its effect on depression varied with the level of perceived social support.

• Journal of the Korean Home Economics Association
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• v.33 no.5
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• pp.241-253
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• 1995

The purpose of this study was to identify how th ADHD variable and family variables influence parents' perception of parental role, family functioning. Subjects were 478 preschoolers at the ages of 3-6 and their teachers and parents. The CTRS-10, the PSI, the FACESⅢ were used. The major findings were as follows ; 1) The variables which ae influential in parental strain were shown in order of the social psychological resource variables, the ADHD variable, and the social demographic variables. The sole ADHD variable's influence was high (β=.26***, increased R2=5.4%). 2) The variables which are influential in parental mastery were shown in order of the social psychological resource variables, the ADHD variable, and the social demographic variables. The sole ADHD variable's influence was high(β=.13*, increased R2=1.5%), also. 3) The variables which are influential in family cohesion and adaptability were shown in order of the social psychological resource variables, the social demographic variables. In both family cohesion and adaptability, the sole ADHD variables' influence was insignificant(β=-.08, increased R2=-0.3%, increased R3=-0.3%). Implications to knowledges as well as recommendations for future research are discussed.

• Korean Journal of Human Ecology
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• v.16 no.3
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• pp.547-562
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• 2007

The purpose of this study was to investigate the relationships of middle-aged men's family and work related variables and satisfaction. Based on the results of the study, the following was concluded ; First, there were significant differences in men's satisfaction across education level, economic variables, and occupation. Second, family related variables, work related variables, and work-family conflict were significantly correlated with satisfaction. In reference to family related variable, satisfaction was higher when marital satisfaction is good, parental stress, adult caring burden, and work-family conflict are lower. In reference to work related variables, satisfaction is higher when job stress is lower, job security is lower, and colleague relationship is good. Third, family related variables, work related variables, and work-family conflict were significantly correlated with mutually one another. Specifically, parental stress is correlated with work related variables. A higher correction was reported between work-family conflict and job stress. Finally, results of multiple regression analysis showed that these variable influenced middle-aged men's satisfaction. Moreover, the degree of explanation for satisfaction increased more, when family and work related variables, and work-family conflict add in individual character variables.

• The Korean Journal of Applied Statistics
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• v.30 no.4
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• pp.555-566
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• 2017

For multivariate datasets with large number of variables, classical dimensional reduction methods such as principal component analysis may not be effective for data visualization. The underlying reason is that the dimensionality of the space of variables is often larger than two or three, while the visualization to the human eye is most effective with two or three dimensions. This paper proposes a working procedure which first partitions the variables into several "latent" clusters, explores individual data subsets, and finally integrates findings. We use R pakacage "ClustOfVar" for partitioning variables around latent dimensions and the principal component biplot method to visualize within-cluster patterns. Additionally, we use the technique for embedding supplementary variables to figure out the relationships between within-cluster variables and outside variables.

• Journal of the Korean Home Economics Association
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• v.26 no.3
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• pp.33-42
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• 1988

The study was to investigate the relationship between clothing variables (Conformity, Modesty, Importance) and environmental variables of Family (the Value Orientations of Family, the Psychological Process of Family), according to sex and region. the subjects were university students in Kyoung nam and Pusan (Male; 397-Pusan 183 and Kyoung nam 214, Female; 401-Pusan 224 and Kyoung Nam 177). Survey method was questionnaires. The data was analyzed with frequency, Pearson's Parson's Correlation, T-test, Multiple Regression using the SPSS. The results were as follows; 1. There was significant difference between clothing Variables in Young nam, but partially significant difference in Pusan. 2. There was partially significant difference between clothing Variables and Environmental Variables of family in each male & female Kyoung nam & Pusan). 3. In the T-test, between clothing Variables and Environmental Variables of family, difference between male and female was shown that female student was higher than male student all of Clothing Variables and male student was higher than female student t in the case of Environmental Variables of family, In the difference between Pusan and Kyoung Nam, male student was shown significant difference in the case of Conformity, materialism and love-Rejection, female student in the case of Modesty, Importance, materialism and Social rising. 4. In the multiple Regression analysis between clothing variables and Environmental Variables of family, clothing voriables partially were effected on the Environmental Variables of family in the cases of male and female in Pusan & Kyoung Nam.

• Korean Journal of Social Welfare
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• v.42
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• pp.254-289
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• 2000

This study conducted a step-wise discriminant analysis to determine which variables play key roles in distinguishing among 3 mutually exclusive delinquent groups - disclosed delinquency group, closed delinquency group, and no delinquency group - and to 'develop a procedure for predicting group membership for new cases whose group membership is undetermined. Variables included in this study were collected by the review of previous empirical studies, which were identified as related to juvenile delinquency. The variables can be classified as character-related variables, family-related variables, school-related variables, peer-related variables, and socioeconomic variables. A sample of 693 youths were employed to conduct the statistical analysis. Out of 35 possible predictors of juvenile delinquency 14 variables were included in the pool of predicting variables. This study used a hold-out sample (n=300) to test if the linear discriminant function classify cases correctly into one of 3 groups. The percentage of cases classified correctly by the discriminant function was turned out to be acceptable in the area of social sciences. Discussions and suggestions were provided in terms of prevention and intervention for juvenile delinquency with focus on the 14 predictor variables.

• Journal of the Korean Home Economics Association
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• v.38 no.1
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• pp.39-49
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• 2000

This research investigated the effect of socio-economic variables and economic distress variables on the university students' coping behavior in meal management. The data used in this research included 544 university students in Ulsan Areas. The independent explanatory power of socio-economic variables was larger than economic distress variables. But the explanatory power was increased in the regression analysis model that was included both the socio-economic variables and the economic distress variables. The influencing variables that effected the level of coping behavior in meal management were the amount of discretionary expenditure, gender, status of housing, employment distress and income distress.

• Communications for Statistical Applications and Methods
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• v.6 no.3
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• pp.755-760
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• 1999

In multivariate stratified sampling surveys it is general to use a few stratification variables which are highly correlated with the important variables at design stage. But there might be some secondary study variables which are not so highly correlated with those stratification variables. In that case it is not efficient to use the same type of estimator due to the secondary variables as the one base on the important variables. A post-stratified estimation is proposed to increase the efficiency of the estimator with existence of secondary variables. The proposed method is illustrated with a set of fishery household population survey data.