• Communications for Statistical Applications and Methods
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• v.17 no.3
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• pp.309-318
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• 2010

The construction of asymptotic confidence intervals is considered for the difference of binomial proportions in two doubly sampled data subject to false-positive error. The coverage behaviors of several likelihood based confidence intervals and a Bayesian confidence interval are examined. It is shown that a hierarchical Bayesian approach gives a confidence interval with good frequentist properties. Confidence interval based on the Rao score is also shown to have good performance in terms of coverage probability. However, the Wald confidence interval covers true value less often than nominal level.

• Journal of the Korean Data and Information Science Society
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• v.6 no.1
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• pp.73-83
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• 1995

We construct the approximate bootstrap confidence intervals for reliability (R) when the distributions of strength and stress are both normal. Also we propose percentile, bias correct (BC), bias correct acceleration (BCa), and percentile-t intervals for R. We compare with the accuracy of the proposed bootstrap confidence intervals and classical confidence interval based on asymptotic normal distribution through Monte Carlo simulation. Results indicate that the confidence intervals by bootstrap method work better than classical confidence interval. In particular, confidence intervals by BC and BCa method work well for small sample and/or large value of true reliability.

• Journal of KIISE
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• v.43 no.5
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• pp.553-561
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• 2016

Several machine learning techniques are able to automatically populate ontology data from web sources. Also the interest for large scale ontology reasoning is increasing. However, there is a problem leading to the speculative result to imply uncertainties. Hence, there is a need to consider the reliability problems of various data obtained from the web. Currently, large scale ontology reasoning methods based on the trust value is required because the inference-based reliability of quantitative ontology is insufficient. In this study, we proposed a large scale OWL Horst reasoning method based on a confidence value using spark, a distributed in-memory framework. It describes a method for integrating the confidence value of duplicated data. In addition, it explains a distributed parallel heuristic algorithm to solve the problem of degrading the performance of the inference. In order to evaluate the performance of reasoning methods based on the confidence value, the experiment was conducted using LUBM3000. The experiment results showed that our approach could perform reasoning twice faster than existing reasoning systems like WebPIE.

• Journal of the Korean Data and Information Science Society
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• v.19 no.3
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• pp.925-936
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• 2008

An association rule mining finds the relation among each items in massive volume database. In generating association rules, the researcher specifies the measurements randomly such as support, confidence and lift, and produces the rules. The rule is not produced if it is not suitable to the one any condition which is given value. For example, in case of a little small one than the value which a confidence value is specified but a support and lift's value is very high, this rule is meaningful rule. But association rule mining can not produce the meaningful rules in this case because it is not suitable to a given condition. Consequently, we creat insignificant error which is not selected to the meaningful rules. In this paper, we suggest clustering technique to association rule measures for finding effective association rules using measure of association.

• Communications for Statistical Applications and Methods
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• v.3 no.1
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• pp.87-99
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• 1996

We construct bootstrap confidence intervals for reliability, R= P{X>Y}, where X and Y are independent normal random variables. One way ANOVA random effect models are assumed for the populations of X and Y, where standard deviations $\sigma_{x}$ and $\sigma_{y}$ are unequal. We investigate the accuracy of the proposed bootstrap confidence intervals and classical confidence intervals work better than classical confidence interval for small sample and/or large value of R.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.5
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• pp.435-443
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• 2010

When testing systems that incorporate probabilistic behavior, it is necessary to apply test inputs a number of times in order to give a test verdict. Interval estimation can be used to assert the correctness of probabilities where the selection of confidence interval is one of the important issues for quality of testing. The Wald interval has been widely accepted for interval estimation. In this paper, we compare the Wald interval and the Agresti-Coull interval for various sizes of samples. The comparison is carried out based on the test pass probability of correct implementations and the test fail probability of incorrect implementations when these confidence intervals are used for probability testing. We consider two-sided confidence intervals to check if the probability is close to a given value. Also one-sided confidence intervals are considered in the comparison in order to check if the probability is not less than a given value. When testing probabilities using two-sided confidence intervals, we recommend the Agresti-Coull interval. For one-sided confidence intervals, the Agresti-Coull interval is recommended when the size of samples is large while either one of two confidence intervals can be used for small size samples.

• The Journal of the Korea Contents Association
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• v.18 no.4
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• pp.279-289
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• 2018

The purpose of this study is to define the implications for improving the performance confidence of nursing students. The study was conducted by surveying a target sample of nursing students. The following data were collected: students' knowledge regarding patient safety, performance confidence, and nursing professional value. The subjects were 309 junior and senior students in the department of nursing science in K University located in G and K province. The data was collected from October 15, 2017 to November 15, 2017. The collected data were analyzed with the SPSS 23.0K using descriptive statistics, t-test, One-Way ANOVA, and Pearson Correlation Coefficient. The study results were that the senior students showed a significantly higher level of knowledge about patient safety than did the junior students (t=3.69, p<.001). With the exceptions of two attributes, education regarding the patient safety and nursing professional value, all other characteristics were variables to a significant difference in performance confidence (p<.05). Moreover, all characteristics except for the school year were variables to a significant difference in nursing professional value (p<.05). A weak correlation was shown between the knowledge regarding patient safety and performance confidence (r=.148, p<.001). A moderate correlation was shown between nursing professional value and performance confidence (r=.456, p<.001). Reinforced education regarding patient safety is recommended to improve the nursing students' performance confidence for clinical practice.

• The Mathematical Education
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• v.62 no.2
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• pp.195-209
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• 2023

This study examined the effect and structural relationship of math teachers' teaching ability and class activity types on learners' value perception, confidence, and interest of mathematics at the student level and teacher level. To this end, data from 2nd graders of korea middle school in TIMSS 2019 were applied to the multilevel structural equation model. As a result of the analysis, the teaching ability of math teachers had a positive effect on value perception, confidence, and interest of mathematics at the student level and teacher level. Also, math value perception and math confidence had a positive effect on math interest. and it was confirmed that the teaching ability of math teachers indirectly had a positive effect on math interest by mediating math value perception and math confidence. In addition, the math class activity of applying what was learned to problems had a positive effect on math value perception, but it had a negative effect on math interest. and the class activity of the same ability group had a positive effect on math confidence and math interest. This study presents meaningful implications for math classes in the school field through a multilevel analysis of the student level and the teacher level.

• Communications for Statistical Applications and Methods
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• v.5 no.3
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• pp.905-926
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• 1998

We propose a modified mid P-value method to reduce the conservativeness for the inference of conditional associations in three-way contingency tables. This improves the ordinary mfd P-value method. For $2{\times} 2${\times} K$ tables, we propose confidence intervals for an assumed common odds ratio based on inverting two separate one-sided tests using the modified mid P-value. Also, an alternative and usually even better ways of constructing intervals, based on Inverting a two-sided test, are presented. The actual probability of coverage of a 100($1-\alpha$)% confidence interval is centered about the nominal level, but the modified mid P-value approach gives actual coverage probability even closer to the nominal level than the ordinary mid P-value approach.

• The Korean Journal of Community Living Science
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• v.27 no.1
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• pp.109-120
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• 2016

This study aims to observe the brand personality of foreign airlines and analyze which brand personality best influences service experience satisfaction, price-value satisfaction, and reusing intention. Moreover, it attempts to determine if there is a difference in service experience satisfaction, price-value satisfaction, and reusing intention according to brand personality. A questionnaire was distributed to 1621 consumers; of these, 1500 were used for final data analysis. Results are as follows. First, a factor analysis was used to investigate the brand personality, and three factors were identified: confidence/competence, sophistication, and dynamic. Second, we investigated the influences a brand personality has on service experience satisfaction, price-value satisfaction, and reusing intention. The confidence/competence of a brand personality showed the greatest influence on service experience satisfaction, price-value satisfaction, and reusing intention. Also, price sensitivity satisfaction had the greatest impact on reusing intentions.