• 충청수학회지
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• 제22권2호
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• pp.171-175
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• 2009

Let $A_1,\;A_2,\;{\cdots},\;A_n$ be a sequence of events on a given probability space. Let $m_n$ be the number of those $A_{i}{^{\prime}}s$ which occur. We establish an improved lower bounds of Univariate Bonferroni-Type inequality by using the linearity of binomial moments $S_1,\;S_2,\;S_3,\;S_4$ and$S_5$.

• 한국신뢰성학회:학술대회논문집
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• 한국신뢰성학회 2000년도 추계학술대회
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• pp.373-373
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• 2000

Bum-in procedures are developed far limited failure populations in which defective products fail soon after they are put in operation and non-defective ones never fail during the technological life of the products. The situation where products are produced from a production process with variable fraction defective is considered. Bum-in schemes guaranteeing pre-specified outgoing quality of products are derived using the mixed binomial prior distribution for the number of defectives in a batch.

• Journal of the Korean Statistical Society
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• 제6권1호
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• pp.3-20
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• 1977

In many applications one is concerned with repeated Bernoulli trials whose parameter (success probability) is usually unknown and has to be estimated from a sample. The probability distribution and statistical inference on the repeated independent Bernoulli trials have been studied extensively for the cases of fixed sample size sampling plan, and inverse binomial sampling plan in which observations are cotinued until a pressigned number of successes are obtained. See, for example, Haldane, Girschick et al., DeGroot and Johnson and Kotz.

• 대한수학회논문집
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• 제22권2호
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• pp.183-194
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• 2007

For an irreducible binomial polynomial $f(x)=x^n-b{\in}K[x]$ with a field K, we ask when does the mth iteration $f_m$ is irreducible but $m+1th\;f_{m+1}$ is reducible over K. Let S(n, m) be the set of b's such that $f_m$ is irreducible but $f_{m+1}$ is reducible over K. We investigate the set S(n, m) by taking K as the rational number field.

• Communications for Statistical Applications and Methods
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• 제8권1호
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• pp.87-96
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• 2001

We consider the empirical Bayes estimation problems with the binomial and normal components when the prior distributions are unknown but are assumed to be in certain families. There may be the families of all distributions on the parameter space or subfamilies such as the parametric families of conjugate priors. We treat both cases and establish the asymptotic optimality for the corresponding decision procedures.

• Communications for Statistical Applications and Methods
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• 제7권3호
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• pp.859-869
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• 2000

In this paper, various methods for finding confidence intervals for p of binomial parameter are reviewed. Also we introduce tow bootstrap confidence intervals for p. We compare the performance of bootstrap methods with other methods in terms of average coverage probability by Monte Carlo simulation. Advantages of these bootstrap methods are discussed.

• Communications for Statistical Applications and Methods
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• 제19권6호
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• pp.761-770
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• 2012

We frequently encounter outcomes of count that have extra variation. This paper considers several alternative models for overdispersed count responses such as a quasi-Poisson model, zero-inflated Poisson model and a negative binomial model with a special focus on a generalized linear mixed model. We also explain various goodness-of-fit criteria by discussing their appropriateness of applicability and cautions on misuses according to the patterns of response categories. The overdispersion models for counts data have been explained through two examples with different response patterns.

• 한국수학교육학회지시리즈D:수학교육연구
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• 제14권2호
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• pp.123-141
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• 2010

This study introduced a coding method for mathematical problems in the TIMSS 1999 Video Study, which used sixteen indicators to analyze mathematical problems in a lesson. Based on this framework for coding, the researcher analyzed three lesson videos on Binomial Theorem taught respectively by three Chinese teachers, and got some features of mathematical problems in these three lessons.

• 품질경영학회지
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• 제19권2호
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• pp.86-95
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• 1991

Empirical Bayes estimation of the binomial parameter ${\theta}$ is considered when the sample size in each component problem is random. The result is applied to the lot acceptance sampling problem in the presence of various kinds of costs including cost for sampling.

• 한국응용곤충학회:학술대회논문집
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• 한국응용곤충학회 2005년도 춘계 학술발표회
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• pp.165-165
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• 2005