• Title, Summary, Keyword: grouped data

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A Study on the Experience of Fundamental Nursing Practice (간호 대학생의 기본 간호 실습 경험에 대한 연구)

  • 한경순;조주연
    • Journal of Korean Academy of Nursing
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    • v.29 no.2
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    • pp.293-303
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    • 1999
  • The purpose of this study was to understand and to explain how were nursing students experienced and accepted the fundemental nursing practice. In addition to, the results of this study are attempted to contribute for offer of basic data in projecting and accomplishing to promote quality practice education. The participants were 79 freshmen of S College of Nursing in kyungi-do. They presented record of feeling and thinking on their the fundemental nursing practice experience. The data were collected from 29, J une to 10, July in 1998. Collected data was analyzed by means of Van Kaam's phenomenological method. The results of this study was founded 423 descriptive expression and they were grouped under 42 common factors and they were grouped under 9 categories. By means of the frequency on the categories. the higher category is Anxiety. next Solemn. Flutter. Pride. Usefulness, Recognition of reality in nursing-system. Lack of practice environment. Self-accusation. Comprehension of nursing spirit were founded. 5 common factors. Tension. Difficulty, Dread. Apprehension, Burden were grouped under Anxiety. 7 common factors, Pledge, Memory, Importance of practice, Sincerity, Restriction of dress, Acceptance, Active attitude were grouped under solemn. 5 common factors, Interest, Strange, Beanimated, Waiting, Curiosity were grouped under Flutter. 5 common factors, Conceit, Self-confidence, Skilled, Worth, Accomplishment were grouped under Pride. 6 common factors, Acknowledge of nursing affairs, Expectation of furture, Fascination of nursing. Acquirement of disposition of nurse, Association of injection, Actual feeling of dept. of nursing were grouped under Recognition of reality in nursing-system. 4 common factors, Lack of practice time, Many persons of practice, Lack of practice instrument, Lack of reality were grouped under Lack of practice envirnment. 5 common factors, Inconvenient, Reflection, Loss of pride, Shyness, Feeling sorry were grouped under Self-accusation. 3 common factors, Utility, Connection of practice and theory, Various experience were grouped under Usefulness. 2 common factors, Comprehension on the dignity of human, Comprehension on a point of view of patient were grouped under Comprehension of nursing spirit. In conclusion, the following recommendation should be necessary a supplementary study to approach on the type of students that has a firm view and care about client prior to clinical nursing practice.

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Nonparametric Tests for Grouped K-Sample Problem

  • Park, Hyo-Il
    • Communications for Statistical Applications and Methods
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    • v.13 no.2
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    • pp.409-418
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    • 2006
  • We propose a nonparametric test procedure for the K-sample problem with grouped data. We construct the test statistics using the scores derived for the linear model based on likelihood ratio principle and obtain asymptotic distribution. Also we illustrate our procedure with an example. Finally we discuss some concluding remarks.

A Comparison Study of the Test for Right Censored and Grouped Data

  • Park, Hyo-Il
    • Communications for Statistical Applications and Methods
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    • v.22 no.4
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    • pp.313-320
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    • 2015
  • In this research, we compare the efficiency of two test procedures proposed by Prentice and Gloeckler (1978) and Park and Hong (2009) for grouped data with possible right censored observations. Both test statistics were derived using the likelihood ratio principle, but under different semi-parametric models. We review the two statistics with asymptotic normality and consider obtaining empirical powers through a simulation study. The simulation study considers two types of models the location translation model and the scale model. We discuss some interesting features related to the grouped data and obtain null distribution functions with a re-sampling method. Finally we indicate topics for future research.

In Silico Analysis of Lactic Acid Secretion Metabolism through the Top-down Approach: Effect of Grouping in Enzyme kinetics

  • Jin, Jong-Hwa;Lee, Jin-Won
    • Biotechnology and Bioprocess Engineering:BBE
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    • v.10 no.5
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    • pp.462-469
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    • 2005
  • A top-down approach is known to be a useful and effective technique for the design and analysis of metabolic systems. In this Study, we have constructed a grouped metabolic network for Lactococcus lactis under aerobic conditions using grouped enzyme kinetics. To test the usefulness of grouping work, a non-grouped system and grouped systems were compared quantitatively with each other. Here, grouped Systems were designed as two groups according to the extent of grouping. The overall simulated flux values in grouped and non-grouped models had pretty similar distribution trends, but the details on flux ratio at the pyruvate branch point showed a little difference. This result indicates that our grouping technique can be used as a good model for complicated metabolic networks, however, for detailed analysis of metabolic network, a more robust mechanism Should be considered. In addition to the data for the pyruvate branch point analysis, Some major flux control coefficients were obtained in this research.

Software Reliability Prediction of Grouped Failure Data Using Variant Models of Cascade-Correlation Learning Algorithm (변형된 캐스케이드-상관 학습 알고리즘을 적용한 그룹 고장 데이터의 소프트웨어 신뢰도 예측)

  • Lee, Sang-Un;Park, Jung-Yang
    • The KIPS Transactions:PartD
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    • v.8D no.4
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    • pp.387-392
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    • 2001
  • This Many software projects collect grouped failure data (failures in some failure interval or in variable time interval) rather than individual failure times or failure count data during the testing or operational phase. This paper presents the neural network (NN) modeling for grouped failure data that is able to predict cumulative failures in the variable future time. The two variant models of cascade-correlation learning (CasCor) algorithm are presented. Suggested models are compared with other well-known NN models and statistical software reliability growth models (SRGMs). Experimental results show that the suggested models show better predictability.

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Jackknife Estimation for Mean in Exponential Model with Grouped and Censored Data

  • Kil Ho Cho;Yong Ku Kim;Seong Kwa Jeong
    • Communications for Statistical Applications and Methods
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    • v.5 no.3
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    • pp.869-878
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    • 1998
  • In this paper, we propose some jackknife estimators for mean in the exponential model with grouped and censored data. Also, we compare the proposed jackknife estimators to other approximate estimators in terms of the mean square error and bias.

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Multivariate Nonparametric Tests for Grouped and Right Censored Data

  • Park Hyo-Il;Na Jong-Hwa;Hong Seungman
    • International Journal of Reliability and Applications
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    • v.6 no.1
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    • pp.53-64
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    • 2005
  • In this paper, we propose a nonparametric test procedure for the multivariate, grouped and right censored data for two sample problem. For the construction of the test statistic, we use the linear rank statistics for each component and apply the permutation principle for obtaining the null distribution. For the large sample case, the asymptotic distribution is derived under the null hypothesis with the additional assumption that two censoring distributions are also equal. Finally, we illustrate our procedure with an example and discuss some concluding remarks. In appendices, we derive the expression of the covariance matrix and prove the asymptotic distribution.

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An development of framework and a supporting tool for organizing Grouped Folksonomy (그룹화된 폭소노미 구축을 위한 프레임워크와 지원도구의 개발)

  • Kang, Yu-Kyung;Hwang, Suk-Hyung
    • Journal of the Korea Society of Computer and Information
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    • v.16 no.5
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    • pp.109-125
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    • 2011
  • A folksonomy is a new classification approach for organizing information by users to freely attach one or more tags to various resources published on the web. Recently, in order to provide useful services and organize the folksonomy data, many collaborative tagging systems based on folksonomy offer additional functionalities for grouping each elements of a folksonomy. In this paper, organization framework for grouped folksonomy is proposed. That is, we suggest the grouped folksonomy model that is an extended folksonomy with the concept of "group" and fundamental operations(Group Aggregation, Group Composition, Group Intersection, Group Difference) for grouping of folksonomy elements. Also, we developed a supporting tool(GFO) that constructs grouped folksonomy and executes fundamental operations. And we introduce some cases using the fundamental operations for grouping of each elements of folksonomy. Based on suggested our approach, we can construct grouped folksonomy and organize and extract useful information from the folksonomy data by grouping each elements of a folksonomy.

Some nonparametric test procedure for the multi-sample case

  • Park, Hyo-Il;Kim, Ju-Sung
    • Journal of the Korean Data and Information Science Society
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    • v.20 no.1
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    • pp.237-250
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    • 2009
  • We consider a nonparametric test procedure for the multi-sample problem with grouped data. We construct the test statistics based on the scores obtained from the likelihood ratio principle and derive the limiting distribution under the null hypothesis. Also we illustrate our procedure with an example and obtain the asymptotic properties under the Pitman translation alternatives. Also we discuss some concluding remarks. Finally we derive the covariance between components in the Appendix.

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A new method for calculating quantiles of grouped data based on the frequency polygon (집단화된 통계자료의 도수다각형에 근거한 새로운 분위수 계산법)

  • Kim, Hyuk Joo
    • Journal of the Korean Data and Information Science Society
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    • v.28 no.2
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    • pp.383-393
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    • 2017
  • When we deal with grouped statistical data, it is desirable to use a calculation method that gives as close value to the true value of a statistic as possible. In this paper, we suggested a new method to calculate the quantiles of grouped data. The main idea of the suggested method is calculating the data values by partitioning the pentagons, that correspond to the class intervals in the frequency polygon drawn according to the histogram, into parts with equal area. We compared this method with existing methods through simulations using some datasets from introductory statistics textbooks. In the simulation study, we simulated as many data values as given in each class interval using the inverse transform method, on the basis of the distribution that has the shape given by the frequency polygon. Using the sum of squares of differences from quantiles of the simulated data as a criterion, the suggested method was found to have better performance than existing methods for almost all quartiles and deciles.