• Journal of Educational Research in Mathematics
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• v.16 no.2
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• pp.139-156
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• 2006

The concept of probability in current school mathematics has been dealt with in the classic viewpoint (mathematical probability) and part of the frequency viewpoint and axiomatic viewpoint have been introduced. However, since the exact understanding of the probability concepts is not possible only with the classic viewpoint, we need to research further on methods to complement classic viewpoint and emphasize various aspects of probability concepts (Lee, Kyung Hwa, 1996). Therefore, this study is to find out optimal computer simulation plans in teaching statistical probability. For the purpose, it examines how the nature of mathematical knowledge may be changed when statistical probability is taught with a use of computer simulation based on the Theory of Didactical Situation presented by Brousseau(1997). Next, it identifies how probability curriculum should be reconstituted for introducing statistical probability through computer simulation. Finally, it develops specific teaching materials that introduce statistical probability using computer simulation based on the results obtained.

• Communications for Statistical Applications and Methods
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• v.7 no.2
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• pp.605-616
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• 2000

Three primary interests frequently raised by mortgage companies are introduced and the corresponding statistical approaches for the default probability in mortgage companies are examined. Statistical models considered in this paper are time series, logistic regression, decision tree, neural network, and discrete time models. Usage of the models is illustrated using an artificially modified data set and the corresponding models are evaluated in appropriate manners.

• Communications for Statistical Applications and Methods
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• v.10 no.2
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• pp.333-339
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• 2003

In this paper, we develop the probability matching priors for the parameters of non-regular Pareto distribution. We prove the propriety of joint posterior distribution induced by probability matching priors. Through the simulation study, we show that the proposed probability matching Prior matches the coverage probabilities in a frequentist sense. A real data example is given.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.3
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• pp.332-338
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• 2018

To perform the Maritime Safety Audi Scheme, $10^{-4}$ was constantly applied without adjustment when evaluating the proximity of the fairway. The necessity of applying the different aberrancy probabilities from the different proximity of the fairway depending on the shape of the route and the size of the ship was validated using marine simulations. Marine simulation was performed to evaluate the validity of statistical analysis-based aberrancy probability according to the different shapes of routes and ship size presented in the previous study. As results, the validity of the criterion of the statistical analysis-based aberrancy probability was confirmed by comparing with the results of simulation-based aberrancy probabilities. The results support that the aberrancy probabilities by the types of a vessel could be different based on the type and size of vessels. The results motivate that further investigation is required to find the reasonable criteria of the aberrancy probabilities for the maritime traffic safety audit according to the fairway shape and the size of the vessel.

• Proceedings of the Korean Statistical Society Conference
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• 2000.11a
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• pp.109-113
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• 2000

We consider the probability that the total population of a Jackson network exceeds a given large value. By using the relation to the stationary distribution, we derive upper and lower bounds on this probability. These bounds imply the stronger logarithmic limit than that in Glasserman and Kou(1995) when several nodes have the same maximal load.

• Proceedings of the Korean Statistical Society Conference
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• 2003.10a
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• pp.201-205
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• 2003

We show how some probability nonreplacement sampling designs can be implemented using nonlinear programming, The efficiency of the proposed approach is compared with selected probability sampling schemes in the literature. The approach is simple to use and appears to have reasonable variance.

• Journal of the Korean Statistical Society
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• v.36 no.3
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• pp.349-355
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• 2007

In this paper we study some important properties of the bivariate generalized hypergeometric probability (BGHP) distribution by establishing the existence of all the moments of the distribution and by deriving recurrence relations for raw moments. It is shown that certain mixtures of BGHP distributions are again BGHP distributions and a limiting case of the distribution is considered.

• Journal of the Korean Statistical Society
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• v.26 no.4
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• pp.555-564
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• 1997

Uncertainty, which arises when little information is revealed, can be represented by a non-additive probability, while risk is described by an additive one. This paper demonstrates that in the presence of uncertainty a steady state probability exists, which implies that we can estimate an average over a long period even under uncertainty. It is also shown that the steady state probability may not be unique in the presence of uncertainty. This implies that the estimated average under uncertainty is less accurate than under risk.

• Journal of the Korean Statistical Society
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• v.32 no.4
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• pp.359-371
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• 2003

We consider the probability that the total population of a stable Jackson network reaches a given large value. By using the fluid limit of the reversed network, we derive new upper and lower bounds on this probability, which are sharper than those in Glasserman and Kou (1995). In particular, the improved lower bound is useful for analyzing the performance of an importance sampling estimator for the overflow probability in Jackson tandem networks. Bounds on the expected time to overflow are also obtained.

• Journal of Educational Research in Mathematics
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• v.20 no.2
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• pp.163-183
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• 2010

It has long been of controversy what the meanings of probability is. And a century has past after the mathematical probability has been at the center of the school curriculum of it. Recently statistical meaning of probability becomes important for various reasons. However the simple modification of its definition is not enough. The computational reasoning of the probability and its practical application needs didactical changes and new instructional transformations along with the modification of it. Most of the current text books introduce probability as a limit of the relative frequencies, a statistical probability. But when the probability computation of the union of two events, or of the simultaneous events is faced on, they use mathematical probability for explanation and practices. Accordingly there is a gap for students in understanding those. Probability is an intuitive concept as far as it belongs to the domain of the experiential frequency. And frequency distribution must be the instructional bases for the (statistical) probability novices. This is what we mean by the probability in accordance with the distribution concepts. First of all, in order to explain the probability of the complementary event we should explain the empirical relative frequency of it first. These are the case for the union of two events and for the simultaneous events. Moreover we need to provide a logic of probabilistic guesses, inferences and decision, which we introduce with the name “the likelihood principle”, the most famous statistical principle. We emphasized this be done through the problems of practical decision making.