• Journal of the Korean Data and Information Science Society
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• v.10 no.2
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• pp.465-472
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• 1999

We considered a bootstrap method for constructing confidenc intervals for a one parameter model using multinomial sampling. The convergence rates or the proposed bootstrap method are calculated for model-based maximum likelihood estimators(MLE) using multinomial sampling. Monte Carlo simulation was used to compare the performance of bootstrap methods with normal approximations in terms of the average coverage probability criterion.

• Journal of the Korean Statistical Society
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• v.31 no.3
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• pp.379-389
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• 2002

For two normal distribution with unknown means and unknown variances, a sequential procedure for estimating the difference of two normal means which satisfies both the coverage probability condition and the $\beta$-protection is proposed under some smoothness of variable imprecision function, and the asymptotic normality of the proposed stopping time after some centering and scaling is given.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.201-206
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• 2003

This study is test for STS304 specimen using bending and torsion state. Rounded specimen and notched specimen including fracture surface investigation was comparatively experimented, fatigue life according to degree of surface finishing was examined. Fatigue fracture probability of notched canilever specimens were predicted by P-S-N curve, median rank and Weibull distribution. And at the relation with the rotational speed and stress, the fatigue life of the test specimen was higher at high speed than low speed If summarize STS304 torsion result of fatigue test, is as following. Fatigue life prediction was available by Weibull statistics distribution, and 50% breakdown probability correlation equation was appeared as following.

• Journal of Environmental Science International
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• v.20 no.3
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• pp.321-327
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• 2011

Bootstrap methods is the computer-based resampling method that estimates the standard errors and confidence intervals of summary statistics using the plug-in principle for assessing the accuracy or uncertainty of statistical estimates, and the BCa method among the Bootstrap methods is known much superior to other Bootstrap methods in respect of the standards of statistical validation. Therefore this study suggests the method of the representation and treatment of uncertainty in flood risk assessment and water resources planning from the construction and application of rainfall frequency analysis model considersing the uncertainty based on the nonparametric BCa method among the Bootstrap methods for the assessement of the estimation of probability rainfall and the effect of uncertainty considering the uncertainty of the parameter estimation of probability in the rainfall frequency analysis that is the most fundamental in flood risk assessement and water resources planning.

• Korean Journal of Construction Engineering and Management
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• v.6 no.1 s.23
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• pp.73-79
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• 2005

This paper, introduces a Stochastic Project Scheduling Simulation system (SPSS III) developed by the author to predict a project completion probability in a certain time. The system integrates deterministic CPM, probabilistic PERT, and stochastic Discrete Event Simulation (DES) scheduling methods into one system. It implements automated statistical analysis methods for computing the minimum number of simulation runs, the significance of the difference between independent simulations, and the confidence interval for the mean project duration as well as sensitivity analysis method in What-if analyzer component. The SPSS 111 gives the several benefits to researchers in that it (1) complements PERT and Monte Carlo simulation by using stochastic activity durations via a web based JAVA simulation over the Internet, (2) provides a way to model a project network having different probability distribution functions, (3) implements statistical analyses method which enable to produce a reliable prediction of the probability of completing a project in a specified time, and (4) allows researchers to compare the outcome of CPM, PERT and DES under different variability or skewness in the activity duration data.

• Journal of the Korean Data and Information Science Society
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• v.21 no.4
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• pp.709-717
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• 2010

The task of association rule mining is to find certain association relationships among a set of data items in a database. There are three primary measures for association rule, support and confidence and lift. In this paper we developed a association rule ranking function using conditional probability increment ratio. We compared our function with several association rule ranking functions by some numerical examples. As the result, we knew that our decision function was better than the existing functions. The reasons were that the proposed function of the reference value is not affected by a particular association threshold, and our function had a value between -1 and 1 regardless of the range for three association thresholds. And we knew that the ranking function using conditional probability increment ratio was very well reflected in the difference between association rule measures and the minimum association rule thresholds, respectively.

• The Korean Journal of Applied Statistics
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• v.19 no.3
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• pp.535-544
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• 2006

We consider use of Bootstrap calibration in the problem of setting a confidence interval for a linear combination of variance components. Based on the the modified large sample(MLS) method by Graybill and Wang(1980), Bootstrap Calibration is applied to improve the coverage probability of the MLS confidence bound when the experiment is balanced and coefficients of a linear combination are positive. Performance of the proposed confidence bound in small sample is investigated by simulation studies.

• Journal of the Korean School Mathematics Society
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• v.1 no.1
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• pp.59-67
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• 1998

Probability and statistics is an important section in mathematics which is deeply related to everyday living, natural science and social science. In spite of its importance, many students will throw away it because it becomes very harder as its step(stage) deepens and probability and statistics' relative importance is very small in Korea-SAT(the test of college entrance in Korea). Therefore, by analyzing the involvement carefully between the curriculum in the elementary, middle, high school and the text book, by studying the problem and improvement direction, it is necessary to investigate an effective teaching method. This study intends to give the students the confidence, interests, and accomplishment motive about probability and statistics field and to make a rational and creative decision-making through mathematical speculation by proposing an effective teaching method through analyzing an existing facts in school's probability and statistics field. The contents of this study are composed of four chapters. Chapter three looks into the mathematical curriculum in the elementary, middle, high school and its teaching meaning, the outline of contents, some tips on teaching and problems and presents an effective and concrete teaching method on the basis of the theoretical background in the chapter two. Chapter four is a conclusive part and gives the general improvement and intentional direction in educating the probability and statistics.

• Communications for Statistical Applications and Methods
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• v.10 no.2
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• pp.277-289
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• 2003

We propose modified exact inferential methods in logistic regression model. Exact conditional distribution in logistic regression model is often highly discrete, and ordinary exact inference in logistic regression is conservative, because of the discreteness of the distribution. For the exact inference in logistic regression model we utilize the modified P-value. The modified P-value can not exceed the ordinary P-value, so the test of size $\alpha$ based on the modified P-value is less conservative. The modified exact confidence interval maintains at least a fixed confidence level but tends to be much narrower. The approach inverts results of a test with a modified P-value utilizing the test statistic and table probabilities in logistic regression model.

• The Korean Journal of Applied Statistics
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• v.2 no.1
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• pp.18-34
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• 1989

The problem of simultaneously estimating the pairwise differences of means of four independent normal populations with equal variances is considered. A statistical computing procedure involving a trivariate t density constructs the exact confidence intervals with simultaneous co verage probability equal to $1-\alpha$. For equal sample sizes, the new procedure is the same as the Tukey studentized range procedure. With unequal sample sizes, in the sense of efficiency for confidence interval lengths and experimentwise error rates, the procedure is superior to the various generalized Tukey procedures.