• Title/Summary/Keyword: conditional probability and independence

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A Didactic Analysis of Conditional Probability (조건부확률 개념의 교수학적 분석과 이해 분석)

  • Lee, Jung-Yeon;Woo, Jeong-Ho
    • Journal of Educational Research in Mathematics
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    • v.19 no.2
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    • pp.233-256
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    • 2009
  • The notions of conditional probability and independence are fundamental to all aspects of probabilistic reasoning. Several previous studies identified some misconceptions in students' thinking in conditional probability. However, they have not analyzed enough the nature of conditional probability. The purpose of this study was to analyze conditional probability and students' knowledge on conditional probability. First, we analyzed the conditional probability from mathematical, historico-genetic, psychological, epistemological points of view, and identified the essential aspects of the conditional probability. Second, we investigated the high school students' and undergraduate students' thinking m conditional probability and independence. The results showed that the students have some misconceptions and difficulties to solve some tasks with regard to conditional probability. Based on these analysis, the characteristics of reasoning about conditional probability are investigated and some suggestions are elicited.

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Semantic analysis of the independency concepts in the probability (확률에서 독립성 개념의 의미 분석)

  • Yoo, Yoon-Jae
    • The Mathematical Education
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    • v.48 no.3
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    • pp.353-358
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    • 2009
  • The article discusses the independence concept occurring in the learning of probability. The author does not distinguishes the independence in the events from the independence in the trials. Instead, the author suggests the physico-empirical independence and the logico-mathematical independence to distinguish between the two concepts.

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3rd, 4th and 5th Graders' Probability Understanding (초등학교 3, 4, 5학년 학생들의 확률 이해 실태)

  • Yoon, Hye-Young;Lee, Kwang-Ho
    • Education of Primary School Mathematics
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    • v.14 no.1
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    • pp.69-79
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    • 2011
  • The purpose of this study is to analyze 3rd, 4th and 5th graders' probability understanding and raise issues concerning instructional methods and search for the possibility of learning probability. For the purpose, a descriptive study through pencil-and-paper test regarding fairness, sample space, probability of event, probability comparison, independence and conditional probability was conducted. The following conclusions were drawn from the results obtained in this study. First, the 3rd, 4th, and 5th grade students scored the highest in the sample space questions. In descending order of skill, the students scored the highest in sample space following probability of events, fairness and probability comparison. Second, however, the level of independence understanding was low. There was no meaningful differences between grades and the conditional probability was the least understood. The independence is difficult to develop naturally according to cognitive development. The conditional probability recognizing the probability of an event changes in non-replacement situations was very difficult for these students. Third, there were significant differences between the 5th graders and the 3rd and 4th graders in the probability comparison questions. It shows that 5th graders understand the concept of proportion when they compare equal ratio probability of an event. The 3rd graers could do different ratio probability of an event more easily than equal ratio probability of an event after they were instructed on probability comparison.

An Analysis of Domestic Research Trends of Probability Education (확률교육에 관한 국내 연구논문의 동향 분석)

  • Park, Minsun;Lee, Eun-Jung
    • Journal of the Korean School Mathematics Society
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    • v.24 no.4
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    • pp.349-367
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    • 2021
  • In this study, 85 studies on probability education from 2000 to 2020 were analyzed by publishing year, journals, research subjects, and research topics. Especially, fundamental probabilistic ideas presented by Batanero et al.(2016) were applied to examine which topics were dominant in domestic probability education research. As a result, it was found that there has been a few research in probability education in Korea during the past 20 years, and the number of human subject studies was slightly more than the number of non-human subject studies. In addition, the analysis of research topics according to the fundamental probabilistic ideas showed that two topics, conditional probability and independence and combinatorial enumeration and counting, were dominant in domestic probability education research. However, while both conditional probability and independence and combinatorial enumeration and counting are introduced to young children using intuitive manners in international probability education research, subjects related to these topics were primarily high school students and pre and in-service teachers. Based on the results of this study, the implications for the goal and the direction of future probability education research were discussed.

CONVERGENCE RATES FOR SEQUENCES OF CONDITIONALLY INDEPENDENT AND CONDITIONALLY IDENTICALLY DISTRIBUTED RANDOM VARIABLES

  • Yuan, De-Mei
    • Journal of the Korean Mathematical Society
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    • v.53 no.6
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    • pp.1275-1292
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    • 2016
  • The Marcinkiewicz-Zygmund strong law of large numbers for conditionally independent and conditionally identically distributed random variables is an existing, but merely qualitative result. In this paper, for the more general cases where the conditional order of moment belongs to (0, ${\infty}$) instead of (0, 2), we derive results on convergence rates which are quantitative ones in the sense that they tell us how fast convergence is obtained. Furthermore, some conditional probability inequalities are of independent interest.

Logit Confidence Intervals Using Pseudo-Bayes Estimators for the Common Odds Ratio in 2 X 2 X K Contingency Tables

  • Kim, Donguk;Chun, Eunhee
    • Communications for Statistical Applications and Methods
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    • v.10 no.2
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    • pp.479-496
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    • 2003
  • We investigate logit confidence intervals for the odds ratio based on the delta method. These intervals are constructed using pseudo-Bayes estimators. The Gart method and Agresti method smooth the observed counts toward the model of equiprobability and independence, respectively. We obtain better coverage probability by smoothing the observed counts toward the pseudo-Bayes estimators in 2$\times$2 table. We also improve legit confidence intervals in 2$\times$2$\times$K tables by generalizing these ideas. Utilizing pseudo-Bayes estimators, we obtain better coverage probability by smoothing the observed counts toward the conditional independence model, no three-factor interaction model and saturated model in 2$\times$2$\times$K tables.

Statistical analysis and its application of bicycle accidents (자전거 교통사고의 통계분석 및 활용)

  • Hong, Chong-Sun;Kim, Moung-Jin
    • Journal of the Korean Data and Information Science Society
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    • v.21 no.6
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    • pp.1081-1090
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    • 2010
  • Most nations including Korean government make a great endeavor to realize low-carbon and green-growth world. We also work hard to expand bicycle facilities and bicycle road in order to increase bicycle transportation rate. Nowadays number of cyclists is increasing but fortunately, bicycle accidents also increase rapidly. Most data of bicycle accidents published by National Police Agency annually are represented as frequencies in two dimensional contingency tables. In this work, risk rates and characteristics of bicycle accidents are analyzed by using concepts of the probability and conditional probability. Especially with numbers of estimated cyclists and registered cars, risk rates of various kinds of bicycle accidents are obtained. Under the assumption of the conditional independence, probability of bicycle accident occurred at realistic situations could be estimated. Furthermore we discuss to reduce bicycle accidents with these results obtained in this work.

Study for independence of hits in professional baseball games (프로야구 경기에서 안타의 독립성에 대한 연구)

  • Kim, Byungsoo;Park, Youngwook;Jang, Nayoung
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.6
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    • pp.1421-1428
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    • 2013
  • In this paper, we would like to test whether the hit at a particular bat has a dependency with the hitting results at the previous bats in professional baseball games. For this purpose, we used the 2011 Korean Baseball League data. We find out that the hitting percentage at a particular bat has no dependency with the hit at the previous bat, after reviewing the conditional probability of hit at each bat and the lift. From the independence test of hits at consecutive bats, and hit at a particular bat with no hits at previous bats, we can conclude that hits at particular bats are not dependent on the hits at previous bats in most cases. Hence, we can safely conclude that a hit at a particular bat is statistically independent from the hits at the previous bats.

Development of an Item Selection Method for Test-Construction by using a Relationship Structure among Abilities

  • Kim, Sung-Ho;Jeong, Mi-Sook;Kim, Jung-Ran
    • Communications for Statistical Applications and Methods
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    • v.8 no.1
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    • pp.193-207
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    • 2001
  • When designing a test set, we need to consider constraints on items that are deemed important by item developers or test specialists. The constraints are essentially on the components of the test domain or abilities relevant to a given test set. And so if the test domain could be represented in a more refined form, test construction would be made in a more efficient way. We assume that relationships among task abilities are representable by a causal model and that the item response theory (IRT) is not fully available for them. In such a case we can not apply traditional item selection methods that are based on the IRT. In this paper, we use entropy as an uncertainty measure for making inferences on task abilities and developed an optimal item selection algorithm which reduces most the entropy of task abilities when items are selected from an item pool.

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BAYESIAN CLASSIFICATION AND FREQUENT PATTERN MINING FOR APPLYING INTRUSION DETECTION

  • Lee, Heon-Gyu;Noh, Ki-Yong;Ryu, Keun-Ho
    • Proceedings of the KSRS Conference
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    • 2005.10a
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    • pp.713-716
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    • 2005
  • In this paper, in order to identify and recognize attack patterns, we propose a Bayesian classification using frequent patterns. In theory, Bayesian classifiers guarantee the minimum error rate compared to all other classifiers. However, in practice this is not always the case owing to inaccuracies in the unrealistic assumption{ class conditional independence) made for its use. Our method addresses the problem of attribute dependence by discovering frequent patterns. It generates frequent patterns using an efficient FP-growth approach. Since the volume of patterns produced can be large, we propose a pruning technique for selection only interesting patterns. Also, this method estimates the probability of a new case using different product approximations, where each product approximation assumes different independence of the attributes. Our experiments show that the proposed classifier achieves higher accuracy and is more efficient than other classifiers.

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