• Korean Journal of Acupuncture
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• v.30 no.1
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• pp.1-8
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• 2013

Objectives : The purpose of the present study was to examine statistical methods used in articles published on the Korean Journal of Acupuncture from 2007 through 2012. Methods : Statistical methods and statistical packages used in original articles applied with descriptive statistics or inferential statistics were organized. Results : Out of a total of 195 original articles, 18 articles used descriptive statistics only and 177 articles used inferential statistics. 142 articles used 12 types of statistical packages. SPSS was used most at 97 times(63.4%). The number of descriptive statistical methods used was a total of 417 and among them 193 were presented as tables(46.3%) and 224 were presented as graphs(53.7%). The number of inferential statistics applied was a total of 256 and analysis of variance was used most at 90 times(35.2%). The number of parametric statistical methods used was a total of 170(75.6%) and that of nonparametric statistical methods used was a total of 55(24.4%). Analysis of variance and two sample t-test were most employed in both clinical and non-clinical research. The number of multiple comparison methods applied was a total of 67 and the number of Scheffe methods among them was most at 26 times(37.7%). Conclusions : In the present study, statistical methods used in the journal over the last six years were examined. The result of this study is considered to be a basic material to be referred to when evaluating the quality of the medical journal.

• Journal of Korean Medicine Rehabilitation
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• v.20 no.4
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• pp.105-130
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• 2010

Objectives : The purpose of this study was to assess the statistical methods errors used in the journal of Oriental Rehabilitation Medicine(JORM) and to identify the types of errors in statistical analysis. Methods : We reviewed quantitative articles that were published in the JORM from January 2005 through October 2009. Those were not used by statistical analysis such as literature studies, case study, review articles were not included in this analysis. A total of 296 articles was reviewed. We evaluated the adequacy and the validity of the statistical techniques with our checklist established be modified Lee's checklist, and three statistical evaluators assessed together to minimize bias. Results : Of the 222 articles, 213 were used in inferential and descriptive statistics. Of those 80% of articles adopting descriptive and inferential statistics were detected having statistical errors. One articles used 1.7 statistical method unit generally. Most frequently employed statistics were student t-test, one way ANOVA. pearson correlation analysis, Mann-whitney U test, paired t-test, and chi-square test in their order. However, most frequent statistics having errors were similar in order. The most common statistic errors were as follow: 1. absence of normality test, 2. misuse between paired test and unpaired test, 3. wrong choice of repeated measures analysis without consideration of time variables, 4, increase of Type I error by using inappropriate multiple test, 5. inappropriate application of discrete or categorical data instead of continuous data in correlation analysis, 6. poor consideration of basic consumption in chi-square test, 7. confusion between frequency comparison and average comparison, 8. mentioning the statistical technique without using it. Conclusions : We found various mistake or misuses in the applications of statistical methodologies in the articles published in the JORM. Careful consideration of statistical use and review from the specialist of statistics are warranted for improving the quality of JORM.

• Journal of Korean Neurosurgical Society
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• v.40 no.4
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• pp.304-308
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• 2006

Statistical analyses used in clinical articles published on the Journal of Korean Neurosurgical Society were identified and appropriateness of statistical aspects in reporting results was assessed. Forty seven clinical articles were selected in this study, which were published from February, 2005 to February, 2006 on the journal. The frequency of statistical analysis was as follows : descriptive statistics only 24 [51.1%]. one type of statistical method 10 [21.3%], two or more methods 13 [27.6%]. An assessment of statistical aspects was performed in 24 clinical articles reporting inferential statistics. Ten articles [41.7%] did not adequately describe or reference all statistical methods used. There were six articles [25.0%] not reporting the confidence level used as the critical criteria of the statistical significance. In thirteen articles [54.2%] it seems more appropriate to implement multivariate analyses in addition to univariate analyses. We recommend that the journal readers should concentrate on improving their knowledge of basic statistics and statistical review for manuscripts submitted should be sought from professionals in the fields of biostatistics and epidemiology.

• Korean Journal of Childcare and Education
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• v.8 no.5
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• pp.157-177
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• 2012

The purpose of this study was to examine the effect of the project approach on the thinking faculty improvement of preschoolers. The subjects in this study were 60 preschoolers who were selected from S kindergarten in Gyeonggi Province. After an experimental group and a control group were organized with 30 preschoolers each, the experimental group engaged in project activities that were based on the project approach, and the control group didn't. As a result of making a comparative analysis, the following findings were given. The preschoolers who participated in the project approach were found to excel over the other preschoolers who didn't participate in perceptual thinking, analytic thinking, synthetical thinking, inferential thinking and thinking faculty. Therefore there should be more consideration to the project approach in the sector of early childhood education, since the activities are effective in improving the thinking faculty of preschoolers.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.4
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• pp.755-767
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• 1997

Analyzing autocorrelated data set is still an open problem. Developing on easy and efficient method for severe positive correlated data set, which is common in simulation output, is vital for the simulation society. Bootstrap is on easy and powerful tool for constructing non-parametric inferential procedures in modern statistical data analysis. Conventional bootstrap algorithm requires iid assumption in the original data set. Proper choice of resampling units for generating replicates has much to do with the structure of the original data set, iid data or autocorrelated. In this paper, a new bootstrap resampling scheme is proposed to analyze the autocorrelated data set : the Threshold Bootstrap. A thorough literature search of bootstrap method focusing on the case of autocorrelated data set is also provided. Theoretical foundations of Threshold Bootstrap is studied and compared with other leading bootstrap sampling techniques for autocorrelated data sets. The performance of TB is reported using M/M/1 queueing model, else the comparison of other resampling techniques of ARMA data set is also reported.

• Research in Mathematical Education
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• v.13 no.2
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• pp.141-150
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• 2009

This study gives opportunity for investigating how student teachers view the teaching profession and how they transfer their pedagogical knowledge into practice. The aim of the study is to investigate the teaching skills student teachers gained in the assessment of micro teaching of their peers. The participants are 30 mathematics student teachers enrolled in the teacher training program in a state university. Document analysis and semi-structured interviews are the research instruments and inferential & descriptive statistics are used for the data analysis. The findings suggest that the qualitative and quantitative peer assessments of student teachers were graded differently which results from the difference of perceptions about teaching and different conceptualizations of the teaching qualifications.

• The Journal of Industrial Distribution & Business
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• v.13 no.11
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• pp.11-19
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• 2022

Purpose: Food security is a dynamic concept, which has continuously integrated new dimensions and levels of analysis over the years; this reflects the wider recognition of its complexities in research and public policy issues. Food insecurity is a major challenge for Ethiopia and for many African countries. This paper aims to identify the roles of social enterprises to overcome food insecurity. Research design, data and methodology: The research has focused on one primary question. What are the role of social enterprises to overcome food insecurity? The survey questionnaire was developed and an interview was made using enumerators. A total sample size of 400 sample households was selected randomly using the method of sampling with probability proportionate to size. Descriptive and inferential statistical analysis methods were used for data analysis. Results: Results of the regression analysis show that all of the hypothesized independent variables are significantly and positively affecting post membership income of the sample households. Conclusions: all stakeholders as government, development actors and academic institutions should closely monitor and support social enterprises/cooperatives technically, financially and materially. By doing so, the full potential and contributions of social enterprises in reducing unemployment and solving the social and environmental problems can be effective.

• Journal of the Korean Data and Information Science Society
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• v.16 no.3
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• pp.665-682
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• 2005

The sample reuse bootstrap technique has been successful to attract both applied and theoretical statisticians since its origination. In recent years a good deal of attention has been focused on the applications of bootstrap methods in regression analysis. It is easier but more accurate computation methods heavily depend on high-speed computers and warrant tough mathematical justification for their validity. It is now evident that the presence of multiple unusual observations could make a great deal of damage to the inferential procedure. We suspect that bootstrap methods may not be free from this problem. We at first present few examples in favour of our suspicion and propose a new method diagnostic-before-bootstrap method for regression purpose. The usefulness of our newly proposed method is investigated through few well-known examples and a Monte Carlo simulation under a variety of error and leverage structures.

• Communications for Statistical Applications and Methods
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• v.24 no.3
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• pp.271-290
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• 2017

We study a bivariate response regression model with arbitrary marginal distributions and joint distributions using Frank and Clayton's families of copulas. The proposed model is used for fitting dependent bivariate data with explanatory variables using the log-odd log-logistic Weibull distribution. We consider likelihood inferential procedures based on constrained parameters. For different parameter settings and sample sizes, various simulation studies are performed and compared to the performance of the bivariate odd-log-logistic-Weibull regression model. Sensitivity analysis methods (such as local and total influence) are investigated under three perturbation schemes. The methodology is illustrated in a study to assess changes on schoolchildren's oral health-related quality of life (OHRQoL) in a follow-up exam after three years and to evaluate the impact of caries incidence on the OHRQoL of adolescents.

• Journal of the Korean Society for information Management
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• v.8 no.2
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• pp.74-95
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• 1991

The purpose of this paper is to study to the nature and function of scientific inquiry and research methods, particularly as they apply to the influencing factors in library schools. For the variables used, they are the average cost per student for training, the total percentage placement in library and library-related work, the average salary for year, and the type of schools. In interpreting data using, t -test analysis of correlation and regression are applied.