• Communications for Statistical Applications and Methods
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• 제19권3호
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• pp.471-478
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• 2012

In this paper, we present a permutation test to select the number of pairs of canonical variates in canonical correlation analysis. The existing chi-squared test is known to be limited to normality in use. We compare the existing test with the proposed permutation test and study their asymptotic behaviors through numerical studies. In addition, we connect canonical correlation analysis to regression and we we show that certain inferences in regression can be done through canonical correlation analysis. A regression analysis of real data through canonical correlation analysis is illustrated.

• 여성건강간호학회지
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• 제17권2호
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• pp.187-194
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• 2011

Purpose: This study investigated the statistical methods and the results had reported correlation/regression analysis in the studies of Korean Journal of Women Health Nursing (KJWHN). Methods: We reviewed 45 studies using correlation/regression analysis for the suitability of the statistical methods and the research purposes, the criteria for analysis of figures, tables and charts had published in the KJWHN from vol 13 (1) in 2007 to vol 15 (4) in 2009. Results: Forty three studies were fitted to their statistical methodology and their research purposes. Eleven studies considered the minimum sample size. Fourteen regression studies used multiple regression and 12 studies used forward method for variable entry. Only one study among the 17 regression studies accomplished scatter plots and residuals examination. Sixteen studies in correlation studies and six studies in regression studies showed some errors in either the title, variables, category of figures, tables and charts. In the regression study, all reported $R^2$ and ${\beta}$ values except one. Conclusion: It was found that there were still statistical errors or articulation errors in the statistical analysis. All reviewers need to be reviewed more closely for detecting errors not only during reviewing process of the manuscript but also periodic publication for the quality of this academic journal.

• 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.

• 한국관개배수논문집
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• 제18권1호
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• pp.25-32
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• 2011

In order to effectively manage the reservoir, reservoir water quality management should be based on physicochemical and configurational characteristics. In this research, correlation between factors affecting the reservoir water quality was examined. Chl-a and COD shows the highest positive correlation. Chl-a and T-P also has a high positive correlation, however Chl-a and T-N show lower correlation relatively. Even though T-N is an important factor for phytoplankton growth which increase Chl-a concentration, corelation of Ch1-a and T-N shows that enough nitrogen in the reservoir isn't no longer limiting factor. The age of reservoir can cause of increasing COD and SS. Embankment height and elevation of reservoirs shows strong negative correlation to water quality. That means reservoir which is higher embankment height and locate in higher elevations is less contaminated. Regression expression was derived with Chl-a and water quality parameters, and height of reservoir. Finally Chl-a was simulated using regression expression and it was a good approach to predict the Chl-a concentration.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2011년도 추계학술대회
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• pp.213-217
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• 2011

The research shows misuse cases of quantitative regression analysis used in QC circle activity and six sigma movement which presents guidelines of correct use for quality practitioners. Additionally, the qualitative regression analysis that responses nonconforming ratio of variable y, is reviewed based on misuse cases for proper use by practitioners in the field. In most cases, there are frequent errors that involve the correlation analysis or ANOVA, regardless of using quantitative regression analysis. In addition, qualitative regression analysis for the nonconforming ratio that has dependent variable of discrete and categorical data, is often applied with quantitative regression and result in ineffective quality improvement.

• 전기학회논문지
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• 제59권4호
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• pp.693-699
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• 2010

General transformer's life is known as paper insulation' life. If a transformer is degraded by these aging factors, it is known that electrical, mechanical and chemical characteristics for transformer's oil-paper are changed. When the kraft paper is aged, the cellulose polymer chains break down into shorter lengths. It causes decrease in both tensile strength and degree of polymerization of paper insulation. The paper breakdown is accompanied by an increase in the content of furanic compounds within the dielectric liquid. In this paper it is aimed at analysis on correlation between aging characteristics for insulating diagnosis of thermally aged paper. For investigating the accelerated aging process of oil-paper samples accelerating aging cell was manufactured for estimating variation of paper insulation during 500 hours at $140^{\circ}C$ temperature. To derive the results, it was performed analysis such as tensile strength(TS), depolymerization(DP), dielectric strength(DS), relative permittivity, water content(WC) and furan compound(FC) for aged paper. Also for analyzing correlation between insulating degradation characteristics, we used linear regression method. As as results of linear regression analysis, there was a close correlation between TS and DP. WC, FC. But dielectric strength was a weak correlation with aging time.

• Journal of Korea Artificial Intelligence Association
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• 제1권2호
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• pp.21-25
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• 2023

The purpose of this study was to compare the performance using multiple regression models to predict the energy consumption of steel industry. Specific independent variables were selected in consideration of correlation among various attributes such as CO2 concentration, NSM, Week Status, Day of week, and Load Type, and preprocessing was performed to solve the multicollinearity problem. In data preprocessing, we evaluated linear and nonlinear relationships between each attribute through correlation analysis. In particular, we decided to select variables with high correlation and include appropriate variables in the final model to prevent multicollinearity problems. Among the many regression models learned, Boosted Decision Tree Regression showed the best predictive performance. Ensemble learning in this model was able to effectively learn complex patterns while preventing overfitting by combining multiple decision trees. Consequently, these predictive models are expected to provide important information for improving energy efficiency and management decision-making at steel industry. In the future, we plan to improve the performance of the model by collecting more data and extending variables, and the application of the model considering interactions with external factors will also be considered.

• Communications for Statistical Applications and Methods
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• 제10권3호
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• pp.695-705
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• 2003

In this article, we propose a regression and correlation analysis via dynamic graphs and implement them in Java Web Start. For the polynomial relations between dependent and independent variables, dynamic graphics are implemented for both polynomial regression and spline estimates for an instant model selection. The results include basic statistics. They are available both as a web-based service and an application.

• 한국임상수의학회지
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• 제27권4호
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• pp.427-434
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• 2010

Correlation is a technique used to measure the strength or the degree of closeness of the linear association between two quantitative variables. Common misuses of this technique are highlighted. Linear regression is a technique used to identify a relationship between two continuous variables in mathematical equations, which could be used for comparison or estimation purposes. Specifically, regression analysis can provide answers for questions such as how much does one variable change for a given change in the other, how accurately can the value of one variable be predicted from the knowledge of the other. Regression does not give any indication of how good the association is while correlation provides a measure of how well a least-squares regression line fits the given set of data. The better the correlation, the closer the data points are to the regression line. In this tutorial article, the process of obtaining a linear regression relationship for a given set of bivariate data was described. The least square method to obtain the line which minimizes the total error between the data points and the regression line was employed and illustrated. The coefficient of determination, the ratio of the explained variation of the values of the independent variable to total variation, was described. Finally, the process of calculating confidence and prediction interval was reviewed and demonstrated.

• Current Research on Agriculture and Life Sciences
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• 제24권
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• pp.49-53
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• 2006

The objective of this study was to present regression equations between reservoir water quality and land use types of the watersheds. In order to derive regression equations, a multiple linear regression analysis was used using observed data from 88 reservoirs in the Kyungpook Provcince. The measured values of BOD, COD, T-N, and T-P were correlated with the areas of land use types. 23 regression equations were obtained for all the water quality items and watershed sizes. The results showed that 2 regression equations have the multiple correlation coefficient(MCC) above 0.90, 10 regression equations have the MCC values from 0.70 to 0.90, 9 equations have the MCC from 0.40 to 0.70, and 2 equations have the MCC from 0.20 to 0.40. The results of this study can be used to estimate reservoir water quality simply and quickly in the planning phase.