• Journal of Korean Society for Quality Management
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• v.43 no.3
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• pp.289-298
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• 2015

Purpose: This study examined the problem of crack formation in the fire control system(FCS) of the K11 objective individual combat weapon(OCIW), using design of experiment analysis. Three hypothesis were considered. The first hypothesis is that bolted joint has an effect on impulse caused by firing the weapon and the second hypothesis is that a short time interval of shooting has an effect on impulse and lastly, the third hypothesis is that a positive correlation has between the bolted joint of the FCS and the impulse. Methods: The relationship between the bolted joint and the impulse cause by firing the weapon were examined experimentally. The first and second hypothesis was tested using correlation analysis and the t-test. Results: Using ANOVA, the first null hypothesis was rejected and the alternative hypothesis was accepted. ANONA confirmed the second null hypothesis. Correlation analysis dismissed the last null hypothesis. A positive correlation between the bolted joint and the impulse caused by shooting the weapon was verified. Conclusion: The bolted joint of the K11 FCS and the barrel of the K11 affect the impulse caused by firing the weapon. A positive correlation was established between the bolted joint of the FCS and the impulse on firing the K11 OICW.

• Communications for Statistical Applications and Methods
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• v.9 no.3
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• pp.765-774
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• 2002

Suppose one is given a vector X of a finite set of quantities $X_i$ which are independent Poisson random variables. A null hypothesis $H_0$ about E(X) is to be tested against an alternative hypothesis $H_1$. A quantity $\sum\limits_{i}w_ix_i$ is to be computed and used for the test. The optimal values of $W_i$ are calculated for three cases: (1) signal to noise ratio is used in the test, (2) normal approximations with unequal variances to the Poisson distributions are used in the test, and (3) the Poisson distribution itself is used. The above three cases are considered to the situations that are without background noise and with background noise. A comparison is made of the optimal values of $W_i$ in the three cases for both situations.

• Journal of the Korean Data and Information Science Society
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• v.13 no.2
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• pp.307-315
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• 2002

Suppose one is given a vector X of a finite set of quantities $X_i$ which are independent Poisson signals. A null hypothesis $H_0$ about E(X) is to be tested against an alternative hypothesis $H_1$. A quantity $$\sum\limits_{i}\omega_ix_i$$ is to be computed and used for the test. The optimal values of $\omega_i$ are calculated for three cases : (1) signal to noise ratio is used in the test, (2) normal approximations with unequal variances to the Poisson distributions are used in the test, and (3) the Poisson distribution it self is used. A comparison is made of the optimal values of $\omega_i$ in the three cases as parameter goes to infinity.

• Korean Journal of English Language and Linguistics
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• v.1 no.3
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• pp.437-456
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• 2001

This paper raises a question on the theoretical background behind the English education at the elementary school level. The Critical Period Hypothesis (CPH), supporting the common belief of the earlier the better in foreign language learning, which has promoted the strong trend toward teaching English in Korean elementary schools, is analyzed to determine whether it provides a comprehensible picture to explain age-related factors and whether it is a valid hypothesis which can be applicable in an EFL situation such as Korea. This paper concludes that CPH itself is still considered as an impending hypothesis full of unresolved issues and that the present educational situation of Korean elementary schools is rather far from the environment in which the ideas of CPH could practically apply, and thus it may be desirable to find alternative theoretical backgrounds from which the educational programs can be developed and further expanded.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.5095-5111
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• 2016

The Probability Hypothesis Density (PHD) filter is a suboptimal approximation and tractable alternative to the multi-target Bayesian filter based on random finite sets. However, the PHD filter fails to track newborn targets when the target birth intensity is unknown prior to tracking. In this paper, a dual detection-guided newborn target intensity PHD algorithm is developed to solve the problem, where two schemes, namely, a newborn target intensity estimation scheme and improved measurement-driven scheme, are proposed. First, the newborn target intensity estimation scheme, consisting of the Dirichlet distribution with the negative exponent parameter and target velocity feature, is used to recursively estimate the target birth intensity. Then, an improved measurement-driven scheme is introduced to reduce the errors of the estimated number of targets and computational load. Simulation results demonstrate that the proposed algorithm can achieve good performance in terms of target states, target number and computational load when the newborn target intensity is not predefined in multi-target tracking systems.

• Communications for Statistical Applications and Methods
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• v.4 no.2
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• pp.427-434
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• 1997

The purpose of this paper is to discuss distribution-free tests of hypothesis that the random samples are identically distributed against the epidemic alternative. But most tests that have been considered are depended only on specific null distribution. Two nonparametric tests are considered and compared with a likelihood ratio test by the empirical powers.

• Proceedings of the PSK Conference
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• 2003.04a
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• pp.117.2-118
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• 2003

Sample size calculations plays an important role in a bioequivalence trials and is determined by considering power under the alternative hypothesis. The regulatory guideline recommends that $2{\times}2$ crossover design is conducted and raw data is log-transformed for statistical analysis. In this paper, we discuss the sample size calculation in $2{\times}2$ crossover design with the log-transformed data.

• The Korean Journal of Applied Statistics
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• v.27 no.4
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• pp.645-653
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• 2014

P-value is the probability of observing a current sample and possibly other samples departing equally or more extremely from the null hypothesis toward postulated alternative hypothesis. When p-value is less than a certain level called ${\alpha}$(= 0:05), researchers claim that the alternative hypothesis is supported empirically. Unfortunately, some findings discovered in that way are not reproducible, partly because the p-value itself is a statistic vulnerable to random variation. Boos and Stefanski (2011) suggests calculating the upper limit of p-value in hypothesis testing, using a bootstrap predictive distribution. To determine the sample size of a replication study, this study proposes thought experiments by simulating boosted bootstrap samples of different sizes from given observations. The method is illustrated for the cases of two-group comparison and multiple linear regression. This study also addresses the reproducibility of the points in the given 95% confidence interval. Numerical examples show that the center point is covered by 95% confidence intervals generated from bootstrap resamples. However, end points are covered with a 50% chance. Hence this study draws the graph of the reproducibility rate for each parameter in the confidence interval.

• Journal of the Korean Chemical Society
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• v.50 no.5
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• pp.385-393
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• 2006

In this study, we analyzed the effects of science inquiry learning that applies open-ended hypothesis-testing learning model in a high school chemistry class of grade 11 in respect of science process skills, science-related attitude, and appreciation towards science class by cognitive level. Open-ended science inquiry learning activities on Metals and their applications unit in Chemistry I were developed and applied to the treatment groups while the conventional science activities were applied to the control groups. Four classes of 92 students in a high school located in Seoul were assigned into the treatment and control groups, respectively. According to the results in the test of science process skills, the students treated with the alternative experiments emphasizing open-ended hypothesis-testing obtained higher scores in experimental design, data conversion and description, and hypothesis test than those with conventional experiments but not in problem cognition and definition and hypothesis fixing'. There was negative effect on science-related attitude due to increased roles and tasks in the open-ended science inquiry learning activities.

• The Korean Journal of Applied Statistics
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• v.22 no.6
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• pp.1249-1263
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• 2009

The power function in sample size determination has to be characterized by an appropriate statistical test for the hypothesis of interest. Nonparametric tests are suitable in the analysis of ordinal data or frequency data with ordered categories which appear frequently in the biomedical research literature. In this paper, we study sample size calculation methods for the Wilcoxon-Mann-Whitney test for one- and two-dimensional ordinal outcomes. While the sample size formula for the univariate outcome which is based on the variances of the test statistic under both null and alternative hypothesis perform well, this formula requires additional information on probability estimates that appear in the variance of the test statistic under alternative hypothesis, and the values of these probabilities are generally unknown. We study the advantages and disadvantages of different sample size formulas with simulations. Sample sizes are calculated for the two-dimensional ordinal outcomes of efficacy and safety, for which bivariate Wilcoxon-Mann-Whitney test is appropriate than the multivariate parametric test.