• Title/Summary/Keyword: statistical analysis method

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A study on applying multivariate statistical method for making casual structure in management information (경영정보의 인과구조 구축을 위한 다변량통계기법 적용에 관한 연구)

  • 조성훈;김태성
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 1996.10a
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    • pp.117-120
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    • 1996
  • The objective of this study is to suggest modified Covariance Structure Analysis that combine with existing Multivariate Statistical Method which is used Casual Analysis Method in Management Information. For this purpose, we'll consider special feature and limitation about Correlation Analysis, Regression Analysis, Path Analysis and connect Covariance Structure Analysis with Statistical Factor Analysis so that theoretical casual model compare with variables structure in collecting data. A example is also presented to show the practical applicability of this approach.

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Comparative Study on Statistical Packages for using Multivariate Q-technique

  • Choi, Yong-Seok;Moon, Hee-jung
    • Communications for Statistical Applications and Methods
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    • v.10 no.2
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    • pp.433-443
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    • 2003
  • In this study, we provide a comparison of multivariate Q-techniques in the up-to-date versions of SAS, SPSS, Minitab and S-plus well known to those who study statistics. We can analyze data through the direct Input method(command) in SAS and use of menu method in SPSS, Minitab and S-plus. The analysis performance method is chosen by the high frequency of use. Widely we compare with each Q-techniques form according to input data, input option, statistical chart and statistical output.

On the Implementation of Maximum-likelihood Factor Analysis

  • Song, Moon-Sup;Park, Chi-Hoon
    • Journal of the Korean Statistical Society
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    • v.9 no.1
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    • pp.13-29
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    • 1980
  • The statistical theory of factor analysis is briefly reviewed with emphasis on the maximum-likelihood method. A modified version of Joreskog(1975) is used for the implementation of the maximum-likelihood method. For the minimization of the conditional minimum function, an adaptive Newton-Raphson method is applied.

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Uncertainty Analysis of Concrete Structures Using Modified Latin Hypercube Sampling Method

  • Yang, In-Hwan
    • International Journal of Concrete Structures and Materials
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    • v.18 no.2E
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    • pp.89-95
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    • 2006
  • This paper proposes a modified method of Latin Hypercube sampling to reduce the variance of statistical parameters in uncertainty analysis of concrete structures. The proposed method is a modification of Latin Hypercube sampling method. This analysis method uses specifically modified tables of random permutations of ranked numbers. In addition, the Spearman coefficient is used to make modified tables. Numerical analysis is carried out to predict the uncertainty of axial shortening in prestressed concrete bridge. Statistical parameters obtained from modified Latin Hypercube sampling method and conventional Latin Hypercube sampling method are compared and evaluated by a numeric analysis. The results show that the proposed method results in a decrease in the variance of statistical parameters. This indicates the method is efficient and effective in the uncertainty analysis of complex structural system such as prestressed concrete bridges.

Type of Statistical Methods and Errors in the Journal of Korean Academy of Fundamentals of Nursing (기본간호학회지 게재 논문의 통계학적 방법 유형과 오류)

  • Choi, Eunhee
    • Journal of Korean Academy of Fundamentals of Nursing
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    • v.22 no.4
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    • pp.452-457
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    • 2015
  • Purpose: In nursing research, studies using statistical methods are required and have increased. In this study, some statistical methods using in nursing study are summarized and appropriate usage is proposed. Methods: Twenty-five original articles from the Journal of Korean Academy of Fundamentals Nursing were reviewed. Statistical methods used in the Journal of Fundamentals Nursing were classified and common errors were presented. Results: Seventy-six statistical analysis were performed in the 25 studies. Among the articles, 28 cases contained errors. Most errors occurred in linear regression analysis and nonparametric analysis. Conclusion: When the use of statistical method is applied inappropriately, the result bring out a serious error. In order to ensure reliability and validity of study, researchers should recognize clear application and usage of statistical methods.

Present Status of Description and Application of Statistics in Clinical study papers in the Journal of Oriental Neuropsychiatry. (동의신경정신과학회지에 발표된 임상연구논문들의 통계방법 기술 및 적용 현황)

  • Cho, Seung-Hun;Hwang, Wei-wan;Lee, Tae-Rim
    • Journal of Oriental Neuropsychiatry
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    • v.18 no.3
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    • pp.15-21
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    • 2007
  • This study was done to review problems in terms of statistical description and statistical application and analysis. Methods; The authors reviewed 42 statistical clinical study papers excluding 12 Overview papers, 75 Descriptive papers, 48 Animal studies out of 177 papers in the Journal of Oriental Neuropsychiatry in the 5 years from 2002 to 2006. Results : 1) 3 papers(7.1%) had no description of statistical method, only P-values, 25 papaers(59.5%) had tables without description of statistical method, 1 paper (2.3%) had no description of statistical method in study method. 2) 10 papers(23.8%) contained problems in terms of statistical application and analysis. 6papers (6/23, 26.0%) for Student t-test, 2 papers(2/7 28.6%)for $X^2$- test, 1 paper(1/15 6.7%) for the analysis of variance, 1 paper(1/6 16.7%) for Pearson correlation contained statistical problems. Conclusion : It was suggested that consultation of investigators with statisticians and more extensive statistical refereeing, the form of the guidelines for description and application of statistics are needed.

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A Diagnostic Method in Principal Factor Analysis

  • Kang-Mo Jung
    • Communications for Statistical Applications and Methods
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    • v.6 no.1
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    • pp.33-42
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    • 1999
  • A method of detecting influential observations in principal factor analysis is suggested. it is based on a perturbation of the empirical distribution function and an adoption of the local influence method. An illustrative example is given.

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Nonlinear damage detection using higher statistical moments of structural responses

  • Yu, Ling;Zhu, Jun-Hua
    • Structural Engineering and Mechanics
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    • v.54 no.2
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    • pp.221-237
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    • 2015
  • An integrated method is proposed for structural nonlinear damage detection based on time series analysis and the higher statistical moments of structural responses in this study. It combines the time series analysis, the higher statistical moments of AR model residual errors and the fuzzy c-means (FCM) clustering techniques. A few comprehensive damage indexes are developed in the arithmetic and geometric mean of the higher statistical moments, and are classified by using the FCM clustering method to achieve nonlinear damage detection. A series of the measured response data, downloaded from the web site of the Los Alamos National Laboratory (LANL) USA, from a three-storey building structure considering the environmental variety as well as different nonlinear damage cases, are analyzed and used to assess the performance of the new nonlinear damage detection method. The effectiveness and robustness of the new proposed method are finally analyzed and concluded.

Multivariate statistical analysis of the comparative antioxidant activity of the total phenolics and tannins in the water and ethanol extracts of dried goji berry (Lycium chinense) fruits

  • Kim, Joo-Shin;Kimm, Haklin Alex
    • Korean Journal of Food Science and Technology
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    • v.51 no.3
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    • pp.227-236
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    • 2019
  • Antioxidant activity in water and ethanol extracts of dried Lycium chinense fruit, as a result of the total phenolic and tannin content, was measured using a number of chemical and biochemical assays for radical scavenging and inhibition of lipid peroxidation, with the analysis being extended by applying a bootstrapping statistical method. Previous statistical analyses mostly provided linear correlation and regression analyses between antioxidant activity and increasing concentrations of phenolics and tannins in a concentration-dependent mode. The present study showed that multiple component or multivariate analysis by applying multiple regression analysis or regression planes proved more informative than linear regression analysis of the relationship between the concentration of individual components and antioxidant activity. In this paper, we represented the multivariate analysis of antioxidant activities of both phenolic and tannin contents combined in the water and ethanol extracts, which revealed the hidden observations that were not evident from linear statistical analysis.