• 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 Integrative Natural Science
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• v.13 no.1
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• pp.27-33
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• 2020

The unsustainable human activities like increased use of automobiles, heavy industrialization and the use of large volumes of fertilizers, chemicals and pesticides in the agricultural land cause climate change problems in one way or another. Under normal circumstances, the heat radiations from the sun will be reflected back. An excessive volume of GHGs in the atmosphere would prevent these radiations from reflecting back. East Asia is facing severe climate change issues in recent times. A lot of climate change problems such as hurricanes and floods have been reported from this region in the last couple of decades. The study aimed at investigating the climate change in East Asia with changing Sea Surface Temperature (SST). The study adopted a quantitative research method with a case study research design where a deliberate focus was made on the East Asia Region. Secondary data was gathered and analyzed to yield both descriptive and inferential statistics. The study concluded that the impact of East Asia Climate variability was significant mainly for some extreme events. Also, the study concluded that there was a significant link between the change of the East Asia climate variability and that of the sea surface temperature. Further, the study concluded that a linear relationship existed between the sea surface temperature and the climate of East Asia. Hence, a linear regression was a significant predictor of the East Asia Climate (EAC) based on changing sea surface temperature. The model revealed that 37.4% of the variations in the climate change index were explained by the changes in the sea surface temperature. The climate was expected to change with a value of 49.48 for a unit change in the sea surface temperature.

• 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.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.573-581
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• 2021

This paper examines the effect of e-service quality on the users of the Facebook marketplace. Users can always have stickiness intention. Stickiness intention is regarded as repetitive visits to and use of a certain website because of a commitment to continue using that website. Hence, we examine and explain the influence of e-service quality variables on stickiness intention. The variables used for e-service quality include efficiency, fulfillment, system availability, and privacy. The researchers related stickiness intention variable to online media users who always use the Facebook marketplace longer than other marketplaces, and users who visit the Facebook marketplace more often than other marketplaces. The method of data analysis was using inferential statistics GeSCA method. The GeSCA method is a Structural Equation Modeling (SEM) technique that can directly analyze latent variables, indicators, and measurement errors. The results of the GeSCA method before the COVID-19 pandemic states that an increase in e-service quality by 77.5% will increase stickiness intention by 61.2%. The results of the GeSCA method after the COVID-19 pandemic states that an increase in e-service quality by 85.2% would increase stickiness intention by 81.1%. This indicates that Facebook marketplace users had more stickiness intention for the Facebook marketplace.

• Physical Therapy Korea
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• v.23 no.2
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• pp.93-99
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• 2016

Background: Parametric statistical procedures are typically conducted under the condition in which a sample distribution is statistically identical with its population. In reality, investigators use inferential statistics to estimate parameters based on the sample drawn because population distributions are unknown. The uncertainty of limited data from the sample such as lack of sample size may be a challenge in most rehabilitation studies. Objects: The purpose of this study is to review the bootstrapping method to overcome shortcomings of limited sample size in rehabilitation studies. Methods: Articles were reviewed. Results: Bootstrapping method is a statistical procedure that permits the iterative re-sampling with replacement from a sample when the population distribution is unknown. This statistical procedure is to enhance the representativeness of the population being studied and to determine estimates of the parameters when sample size are too limited to generalize the study outcome to target population. The bootstrapping method would overcome limitations such as type II error resulting from small sample sizes. An application on a typical data of a study represented how to deal with challenges of estimating a parameter from small sample size and enhance the uncertainty with optimal confidence intervals and levels. Conclusion: Bootstrapping method may be an effective statistical procedure reducing the standard error of population parameters under the condition requiring both acceptable confidence intervals and confidence level (i.e., p=.05).

• The Journal of Economics, Marketing and Management
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• v.5 no.2
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• pp.1-9
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• 2017

This study has reviewed the "A survey on the relation between the employees' viewpoint with knowledge management and cultural intelligence among the employees working in Social Security Organization of Ardabil". The present study is functional in terms of objective and the method is descriptive and survey. This has asked the others' ideas and viewpoints concerning a specific subject and has analyzed them. About the nature and the method used, the present research is of correlation research. The population applied in this research includes all employees working in Social Security Organization of Ardabil consisting of 400. The method used for sampling is simple random sampling. To collect the information in the first step of the research the library method has been used. In this research the data has been collected through standard questionnaires. Then, via descriptive and inferential statistics the research data has been characterized and regarding the spatial scaling of the measurement to test the hypothesis the, correlation analysis of Pearson has been used and also to specify the reliability of the questionnaire the Chronbach's Alpha has been taken in use and the SPSS software to analyze the data also. The findings resulted from the study showed that there is a significant relation between the factors concerning employees' efficiency with knowledge management and the cultural intelligence and all hypotheses was confirmed.

• Communications for Statistical Applications and Methods
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• v.13 no.3
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• pp.503-512
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• 2006

In this paper, the Inverse Weibull distribution parameters have been estimated using a new estimation technique based on the non-parametric kernel density function that introduced as an alternative and reliable technique for estimation in life testing models. This technique will require bootstrapping from a set of sample observations for constructing the density functions of pivotal quantities and thus the confidence intervals for the distribution parameters. The performances of this technique have been studied comparing to the conditional inference on the basis of the mean lengths and the covering percentage of the confidence intervals, via Monte Carlo simulations. The simulation results indicated the robustness of the proposed method that yield reasonably accurate inferences even with fewer bootstrap replications and it is easy to be used than the conditional approach. Finally, a numerical example is given to illustrate the densities and the inferential methods developed in this paper.

• 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.

• Journal of the Korean Data and Information Science Society
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• v.21 no.4
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• pp.813-818
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• 2010

The least squares estimation method for model parameters under failure step-stress accelerated life tests is studied and a numerical example will be given to illustrate the proposed inferential procedures under the compound linear plans proposed as an alternative to the optimal quadratic plan, assuming that the exponential distribution with a quadratic relationship between stress and log-mean lifetime. The proposed compound linear plan for constant stress accelerated life tests and 4:2:1 plan are compared for various situations. Even though the compound linear plan was proposed under constant stress accelerated life tests, we found that this plan did well relatively in failure step-stress accelerated life tests.

• Journal of Science Education
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• v.41 no.1
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• pp.135-151
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• 2017

This study set out to investigate the challenges to science teacher's teaching practices in the Anglophone sub-system of education in Cameroon secondary schools. A sample of 331 of these teachers was selected using the purposive sampling method. Data was collected by use of a questionnaire and was subjected to inferential analysis. The major findings from the multiple regression were challenges associated with the size and management of a science class have an effect on the teaching practices of a science teacher. However, challenges with availability of instructional resources did not have an effect on science teaching practices. Recommendations to solve the identified drawbacks include the provision of more classrooms to accommodate the ever growing population of students and the organization of many seminars through which teachers could be educated on how to handle classroom problems and improvise when necessary.