• Journal of Fashion Business
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• v.11 no.3
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• pp.69-78
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• 2007

This study explored the perceptions of Korean college women concerning their clothing deprivation and clothing decision factors. A convenience sample was used consisting of 101 female college students aged from 18 to 36 years, with a mean age of 20.78 (SD = 4.24). Descriptive statistics were used to develop a profile of the participants. To test the research objectives, multivariate analysis of variance (MANOVA), using Wilk's lambda criterion was conducted for the study. The results indicated that a college woman's year significantly influences her perceived clothing deprivation, at p =0.003 (Wilk's lambda). There was a significant positive correlation (r = 0.24, p= 0.02) between college year and perceived clothing deprivation for special occasion clothes. The two clothing decision factors clothes that fit me well and clothes that look best on me were found to be the top two factors determining clothing decisions for the study participants.

• The Korean Journal of Applied Statistics
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• v.12 no.1
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• pp.97-107
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• 1999

프로파일 분석은 반복측정 자료를 분석하는데 있어서 널리 사용되는 다변량 분석모형이다. 프로파일 분석에서는 처리 그룹간의 비교와 반응 프로파일의 평행성 검정을 위해서 4가지 검정통계량이 널리 사용되고 있다. 이들 검정통계량은 Wilks의 통계량($\Lambda$), Pillai's Trace 통계량(V), Hotelling-Lawley Trace 통계량(U), Roy's Maximum Root 통계량($\Theta$ )이다. 그 동안 이들 통계량들을 비교하기 위한 여러 연구가 있었지만 주로 일반적인 다변량 분산분석 모형에 근거한 비교였다. 본 논문에서는 자료가 반복측정 자료이고 우리의 관심이 프로파일 분석에 있을 때에 이 4가지 통계량의 비교에 초점을 맞추었다.

• The Korean Journal of Applied Statistics
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• v.15 no.1
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• pp.9-20
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• 2002

This paper is to verify the effects of English immersion program through the case study of the three and an half week English camp run by Hongik University. The student's proficiency in English varies according to different factors. Another goal of this paper is to pin down certain objective factors that have an effect on the English proficiency and the improvement of the proficient. The generalized linear model(GLM) is adopted for the related analyses in this paper.

• Journal of the Korean earth science society
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• v.40 no.6
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• pp.606-612
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• 2019

In this study, to estimate the occurrence of frost that has a negative effect on th growth of crops, we constructed to the statistical model. We factored such various meteorological elements as the minimum temperature, temperature at 18:00, temperature at 21:00, temperature at 24:00, average wind speed, wind speed at 18:00, wind speed at 21:00, amount of cloud, amount of precipitation within 5 days, amount of precipitation within 3 days, relative humidity, dew point temperature, minimum grass temperature and ground temperature. Among the diverse variables, the several weather factors were selected for frost occurrence estimation model using statistical methods: T-test, Variable importance plot of Random Forest, Multicollinearity test, Akaike Informaiton Criteria, and Wilk's Lambda values. As a result, the selected meteorological factors were the amount of cloud, temperature at 24:00, dew point temperature, wind speed at 21:00. The accuracy of the frost occurrence estimation model using Random Forest was 70.6%. When it applied to the main production areas of vegetables, a estimation accuracy of the model was 65.2 and 78.6%.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.305-315
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• 2021

This article aims to explore the contribution of social media value to a company's financial performance in a digital environment economy since the awareness of companies and investors in the use of social media opens up new mechanisms for disseminating information. Quantitative method is used in this study with Multivariate Analysis of Variance as the analysis tool. The data used is secondary data gathered from Indonesia Stock Exchange (IDX) using 308 companies as samples. In the multivariate test, four kinds of multivariate significance tests were carried out, namely Pillai Trace, Wilk Lambda, Hotelling's Trace, and Roy's Largest Root. It was found that social media value has a small contribution in the difference of the level of profitability and the value of the company in Indonesia, but it doesn't have a contribution to the difference of the level of liquidity. The contribution was an implication of online Word of Mouth (WOM) motives which are interrelated with signal theory and as additional information for investors in relation to single-person decision theory. This study provides an insight into the importance of social media management considering that the world of digital economy will continue to develop, so companies in Indonesia need to take advantage of these opportunities.

• Journal of Korean Academy of Nursing
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• v.45 no.3
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• pp.347-356
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• 2015

Purpose: In this study, the effectiveness of a motivational interviewing smoking cessation YOU-TURN program for adolescents was examined. The program was based on the self-determination theory. Methods: The study was carried out with a nonequivalent control group pretest-posttest design. Participants in the present study were 136 high school students living in D city. The students were assigned to the experimental group (n=52) who participated in the motivational interviewing smoking cessation YOU-TURN program based on self-determination theory, or to the control group (n=84) who participated in a general smoking cessation program. Data were collected from September 1, 2013 through April 30, 2014. Collected data were analyzed using SPSS PC+ 21.0 with Chi-square test, Fisher's exact test, t-test, Mann-Whitney U test, Repeated Measures ANOVA, and MANOVA-Wilk's Lambda. Results: The experimental group had a significant increase in basic psychological needs, and duration of quitting-smoking in comparison with the control group. The experimental group had a significant decrease in cigarettes smoked per day and cotinine in urine in comparison with the control group. Conclusion: The motivational interviewing YOU-TURN program, when delivered to adolescents who smoked, was effective in discouraging smoking, and can be utilized as an effective nursing intervention for adolescents who smoke.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.18 no.2
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• pp.170-177
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• 2009

The objective of this study is to evaluate an acoustic emission (AE) source characterization and fracture behavior of the SM45C steel by using back-propagation neural network (BPN). In previous research Ref. [8] about k-nearest neighbor classifier (k-NNC) continuity, we used K-means clustering method as an unsupervised learning method for obtaining multi-variate AE main data sets, such as AE counts, energy, amplitude, risetime, duration and counts to peak. Similarly, we applied k-NNC and BPN as a supervised learning method for obtaining multi-variate AE working data sets. According to the error of convergence for determinant criterion Wilk's ${\lambda}$, heuristic criteria D&B(Rij) and Tou values are discussed. As a result, in k-NNC before fracture signal is detected or when fracture signal is detected, showed that produce some empty classes in BPN. And we confirmed that could save trouble in AE signal processing if suitable error of convergence or acceptable encoding error give to BPN.

• Journal of the Korea Safety Management & Science
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• v.11 no.1
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• pp.27-33
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• 2009

A study of fracture to material is getting interest in nuclear and aerospace industry as a viewpoint of safety. Acoustic emission (AE) is a non-destructive testing and new technology to evaluate safety on structures. In previous research continuously, all tensile tests on the pre-defected coupons were performed using the universal testing machine, which machine crosshead was move at a constant speed of 5mm/min. This study is to evaluate an AE source characterization of SM45C steel by using k-nearest neighbor classifier, k-NNC. For this, we used K-means clustering as an unsupervised learning method for obtained multi -variate AE main data sets, and we applied k-NNC as a supervised learning pattern recognition algorithm for obtained multi-variate AE working data sets. As a result, the criteria of Wilk's $\lambda$, D&B(Rij) & Tou are discussed.

• Journal of the Korean Data and Information Science Society
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• v.27 no.6
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• pp.1565-1571
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• 2016

This paper is an empirical study of chinese consumers' lifestyle by country of origin effect of mobile phone. The data we analyze in this paper was collected and studied in Kim et al. (2006, 2007). We classify the respondents into the four groups according to the responses of country of origin effect of mobile phone. The four groups are group K (preference in made in Korea), group J (preference in made in Japan), group U (preference in made in USA), and group C (preference in made in China). One-way ANOVA and stepwise discriminant analysis are applied to classify the training sample which consists of 89 lifestyle variables and two personnel information. It is observed that group K is more open-minded, out front, aggressive, and self-assertive compared to group C.