• Communications for Statistical Applications and Methods
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• v.16 no.1
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• pp.127-135
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• 2009

It is necessary to forecast the amount of the maximum electricity demand for stabilizing the flow of electricity. The time series data was collected from the Korea Energy Research between January 2000 and December 2006. The data showed that they had a strong linear trend and seasonal change. Winters seasonal model, ARMA model were used to examine it. Root mean squared prediction error and mean absolute percentage prediction error were a criteria to select the best model. In addition, a nonstationary generalized extreme value distribution with explanatory variables was fitted to forecast the maximum electricity.

• Fourth Industrial Review
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• v.3 no.2
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• pp.1-10
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• 2023

Purpose - The main purpose of the paper is to examine the variables affecting carbon emissions in different nations around the world. Research design, data, and methodology - To measure its impact on carbon emissions, secondary data has data of the top 50 Countries have been taken. The stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model have been used to quantify the factors that affect carbon emissions. A modified version using Industry 4.0 and region in fundamental STIRPAT model has been applied with the ordinary least square approach. The outcome has been measured using both the basic and extended STIRPAT models. Result - Technology found a positive determinant as well as statistically significant at the alpha level of 0.001models indicating that technological innovation helps reduce carbon emissions. In total, 4 models have been derived to test the best fit and find the highest explaining capacity of variance. Model 3 is found best fit in explanatory power with the highest adjusted R2 (97.95%). Conclusion - It can be concluded that the selected explanatory variables population and Industry 4.0 are found important indicators and causal factors for carbon emission and found constant with all four models for total CO2 and Co2 per capita.

• Journal of Environmental Science International
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• v.25 no.2
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• pp.191-216
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• 2016

Since prolonged exposure to elevated ozone ($O_3$) concentrations is known to be harmful to human health, appropriate control strategies for ozone are needed for the non-attainment area such as Seoul, Korea. The goal of this research is to assess factors linked with the 1-hour ozone exceedance through a decision tree model. Since ozone is a secondary pollutant, lag times between ozone and explanatory variables for ozone formation are taken into account in the model to improve the accuracy of the simulation. Results show that while ozone concentrations of the previous day and $NO_2$ concentrations in the morning are major drivers for ozone exceedances in the early afternoon, meteorology plays more important role for ozone exceedances in the late afternoon. Results also show that a selection of lag times between ozone and explanatory variables affect the accuracy of predicting 1-hour ozone exceedances. The result analyzed in this study can be used for developing control strategies of ozone in Seoul, Korea.

• Journal of Korean society of Dental Hygiene
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• v.13 no.5
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• pp.827-833
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• 2013

Objectives : The purpose of the study is to investigate the relationship between self-leadership in clinical practice and stress in dental hygiene majoring students. Methods : Subjects were 250 dental hygiene majoring students in J area from March 20 to April 20, 2012. Data were analyzed using the statistical package SPSS WIN 12.0 for frequency, mean and standard deviation analysis, one-way ANOVA and multiple regression. Results : There were significant differences between Satisfaction and clinical practice, practice and major stress factors(p<0.01). There were significant differences between practices, satisfaction, and self-expectations(p<0.001). The explanatory power of the model was 9%(p<0.05). The combination of self-leadership, activity, interpersonal factors were very important factors and the explanatory power of the model was 8%(p<0.001). Conclusions : Self-leadership is able to decrease stress. Self-leadership is very important in clinical practice in dental hygiene majoring students.

• Journal of Korean Philosophical Society
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• v.141
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• pp.167-185
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• 2017

Chu Hsi inherited the proposition of Cheng Yi, and it spent him over ten years to finish writing the works of Xi Ming Jie, thus, making the thought of "Li Yi Fen Shu" bethe explanatory model of Xi Ming, therefore, playing the role to determine the tone of Xi Ming. At first, the thought of "Li Yi Fen Shu is a concept to embody the ethical significance of Xi Ming. But in terms of all the discussion about "Li Yi Fen Shu" of Chu Hsi in his life, this proposition is not only for the ethical significance of Xi Ming, but also includes much more general philosophical significance, revealing the general and special relationship of things. The former is the narrow "Li Yi Fen Shu", but the latter is the generalized one. This article won't discuss the generalized one, and it will take the narrow one as the research object. In the past research in academic circles, some scholars thinks that the proposition of "Li Yi Fen Shu" accords with the aim of Xi Ming, some others don't think so. Contrary to both of the two views, this article thinks that there is some conformity and inconformity between the explanatory model of "Li Yi Fen Shu" of Chu Hsi and the aim of Xi Ming. In other words, Contributions and limitations coexist when Chu Hsi explains Xi Ming in the model of "Li Yi Fen Shu", and there is not only the development to the intention of Xi Ming, but alsothe far meaning away from the aim of Xi Ming.

• The Korean Journal of Applied Statistics
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• v.20 no.2
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• pp.229-244
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• 2007

Among the small area estimation methods, it has been known that hierarchical Bayesian(HB) approach is the most reasonable and effective method. However any model based approaches need good explanatory variables and finding them is the key role in the model based approach. As the lacking of explanatory variables, adopting the spatial terms in the model was introduced. Here in this paper, we evaluate the model based methods with/without spatial terms using the diagnostic methods which were introduced by Brown et al. (2001). And Economic Active Population Survey(2005) is used for data analysis.

• Korean Journal of Occupational Health Nursing
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• v.29 no.4
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• pp.262-272
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• 2020

Purpose: This study aims to investigate the degree of job demand, job resources, burnout, and the organizational commitment of administrative nurses based on the job demands-resources model. Further, it seeks to confirm the influencing factors affecting nurses' burnout and organizational commitment. Methods: The participants were 188 administrative nurses working at hospitals (one tertiary hospital and six general hospitals) located in D City. The collected data were analyzed with IBM SPSS Statistics 23.0 using frequency, percentage, mean, standard deviation, t-tests, ANOVA, Pearson's correlation coefficient, and multiple regression analysis. Results: The influential factors of burnout were role conflict (β=.50), job demand (β=.18), job position (β=-.17, team leaders and above), and social support (β=-.15). The regression model had an explanatory power of 59%. The influential factors of organizational commitment were appropriate rewards (β=.59), job position (β=.15, team leader or above), working department (β=.14, referral center and health screening administration department), and social support (β=.18). The regression model had an explanatory power of 59.5%. Conclusion: The results support the job demands-resources model, and interventions should be developed to decrease job demand and provide sufficient job resources.

• Journal of the Korean Data and Information Science Society
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• v.25 no.2
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• pp.403-410
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• 2014

Binary logistic regression analysis is a statistical technique that explains binary response variable by quantitative or qualitative explanatory variables. In the binary logistic regression model, the probability that the response variable equals, say 1, one of the binary values is to be explained as a transformation of linear combination of explanatory variables. This is one of big barriers that non-statisticians have to overcome in order to understand the model. In this study, an educational tool is developed that explains the need of the binary logistic regression analysis using Excel VBA. More precisely, this tool explains the problems related to modeling the probability of the response variable equal to 1 as a linear combination of explanatory variables and then shows how these problems can be solved through some transformations of the linear combination.

• Journal of the Korean Chemical Society
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• v.68 no.2
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• pp.107-116
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• 2024

The purpose of this study is to analyze changes in pre-service chemistry teachers' cognition of the nature of model in the evaluation and modification process of model using technology. Changes in cognition of the nature of model were analyzed focusing on the 'Abstraction' and 'Simplification' of the 'Representational aspect', 'Interpretation', 'Reasoning', 'Explanation' and 'Quantification' of the 'Explanatory aspect' that were deemed insufficient for pre-chemistry teachers in previous study. For this purpose, 19 third-year pre-service chemistry teachers at a teacher's college in Chungcheongbuk-do were asked to evaluate the model related to Boyle's law developed using technology, revise the model based on the evaluation results, and make a final evaluation. As a result of the study, it was confirmed that pre-service chemistry teachers' cognition of 'Simplification' of the 'Representational aspect' and 'Interpretation', 'Explanation', and 'Quantification' of the 'Explanatory aspect' changed positively through the evaluation and modification process of the model. Therefore, it was found that the evaluation and modification process of the model plays a key role in changing the cognition of the nature of model. However, there was little change in cognition of 'Abstraction' of the 'Representational aspect' and 'Reasoning' of the 'Explanatory aspect'. The cognition of these factors can be seen as more difficult to change than the cognition of other factors. To solve this problem, more sophisticated educational design for pre-service chemistry teachers is needed.

• Communications for Statistical Applications and Methods
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• v.2 no.2
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• pp.296-302
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• 1995

When heteroscedasticity occurs in random effects linear model, the error variance may depend on the values of one or more of the explanatory variables or on other relevant quantities such as time or spatial ordering. In this paper we derive a score test as a diagnostic tool for detecting non-constant error variance in random effefts linear model based on the model expansion on error variance. This score test is compared to loglikelihood ratio test.