• Title/Summary/Keyword: statistical graphs

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Development of Numerical and Graph Interpretation Skills - Prerequisites for Statistical Literacy

  • Watson, Jane M.;Kelly, Ben A.
    • Research in Mathematical Education
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    • v.10 no.4 s.28
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    • pp.259-288
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    • 2006
  • This study considers the performance of students in Grades 5 to 10 on four tasks assessing students' ability to evaluate data presented in numerical form, for example, in a list or table, or in graphical form, for example, in a frequency graph or scatter graph. The ability to tell a story from data or a graph is an important aspect of statistical literacy. The samples provide the opportunity to consider the association of two pairs of items, one from each type of interpretation, numerical and graphical. Educational implications for the outcomes and the classroom use of the items are considered.

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Statistical Literacy of Fifth and Sixth Graders in Elementary School about the Beginning Inference from a Pictograph Task ('그림그래프에서 추론하기' 과제에서 나타나는 초등학교 5, 6학년 학생들의 통계적 소양)

  • Moon, Eunhye;Lee, Kwangho
    • Education of Primary School Mathematics
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    • v.22 no.3
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    • pp.149-166
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    • 2019
  • The purpose of this study is to analyze the statistical literacy in elementary school students when they beginning inference. Picto-graphs provide statistical information and often data-related arguments they certainly qualify as objects for interpretation, for critical evaluation, and for discussion or communication of the conclusions presented. For research, the inference from pictograph task was designed and statistical literacy standards for evaluating the student's level was presented based on prior studies. Evaluating student's statistical literacy is meaningful in that it can check their current level. To know the student's current level can help them achieve a higher level of performance. The outcomes of this research indicate that pictograph can provide a basis for rich tasks displaying not only student's counting skills but also their appreciation of variation and uncertainty in prediction. Raising statistical thinking by students is an important goal in statistical education, and the experience of informal statistical reasoning can help with formal statistical reasoning that will be learned later. Therefore, the task about the inference from a pictograph, discussions on statistical learning of elementary school children are expected to present meaningful implications for statistical education.

Statistical Methods Used in Articles of the Korean Journal of Acupuncture (경락경혈학회지 게재논문에 사용된 통계방법)

  • Kim, Jung-Eun;Kang, Kyung-Won;Lee, Min-Hee;Lee, Sanghun
    • Korean Journal of Acupuncture
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    • v.30 no.1
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    • pp.1-8
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    • 2013
  • Objectives : The purpose of the present study was to examine statistical methods used in articles published on the Korean Journal of Acupuncture from 2007 through 2012. Methods : Statistical methods and statistical packages used in original articles applied with descriptive statistics or inferential statistics were organized. Results : Out of a total of 195 original articles, 18 articles used descriptive statistics only and 177 articles used inferential statistics. 142 articles used 12 types of statistical packages. SPSS was used most at 97 times(63.4%). The number of descriptive statistical methods used was a total of 417 and among them 193 were presented as tables(46.3%) and 224 were presented as graphs(53.7%). The number of inferential statistics applied was a total of 256 and analysis of variance was used most at 90 times(35.2%). The number of parametric statistical methods used was a total of 170(75.6%) and that of nonparametric statistical methods used was a total of 55(24.4%). Analysis of variance and two sample t-test were most employed in both clinical and non-clinical research. The number of multiple comparison methods applied was a total of 67 and the number of Scheffe methods among them was most at 26 times(37.7%). Conclusions : In the present study, statistical methods used in the journal over the last six years were examined. The result of this study is considered to be a basic material to be referred to when evaluating the quality of the medical journal.

Economic-Statistical Design of VSSI$\bar{X}$ Control Charts Considering Two Assignable Causes (두 개의 이상원인을 고려한 VSSI$\bar{X}$ 관리도의 경제적-통계적 설계)

  • Lee, Ho-Joong;Lim, Tae-Jin
    • Journal of Korean Institute of Industrial Engineers
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    • v.31 no.1
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    • pp.87-98
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    • 2005
  • This research investigates economic-statistical characteristics of variable sampling size and interval (VSSI)$\bar{X}$charts under two assignable causes. A Markov chain approach is employed in order to calculate average run length (ARL) and average time to signal (ATS). Six transient states are derived by carefully defining the state. A steady state cost rate function is constructed based on Lorenzen and Vance(1986) model. The cost rate function is optimized with respect to six design parameters for designing the VSSI $\bar{X}$ charts. Computational experiments show that the VSSI $\bar{X}$ chart is superior to the Shewhart $\bar{X}$ chart in the economic-statistical sense, even under two assignable causes. A comparative study shows that the cost rate may increase up to almost 30% by overlooking the second cause. Critical input parameters are also derived from a sensitivity study and a few guideline graphs are provided for determining the design parameters.

The performance of Bayesian network classifiers for predicting discrete data (이산형 자료 예측을 위한 베이지안 네트워크 분류분석기의 성능 비교)

  • Park, Hyeonjae;Hwang, Beom Seuk
    • The Korean Journal of Applied Statistics
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    • v.33 no.3
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    • pp.309-320
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    • 2020
  • Bayesian networks, also known as directed acyclic graphs (DAG), are used in many areas of medicine, meteorology, and genetics because relationships between variables can be modeled with graphs and probabilities. In particular, Bayesian network classifiers, which are used to predict discrete data, have recently become a new method of data mining. Bayesian networks can be grouped into different models that depend on structured learning methods. In this study, Bayesian network models are learned with various properties of structure learning. The models are compared to the simplest method, the naïve Bayes model. Classification results are compared by applying learned models to various real data. This study also compares the relationships between variables in the data through graphs that appear in each model.

UNCERTAINTIES IN THE STAR-COUNT ANALYSIS

  • Hong, Seung-Soo;Lee, See-Woo
    • Journal of The Korean Astronomical Society
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    • v.21 no.2
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    • pp.155-171
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    • 1988
  • We have examined how sensitively the extinction value determined by the method of star-count depends on such factors as the plate limit, the size of counting reseau, the non-linearity in the number distribution of stars with magnitude, and the angular resolution demanded by the given problem. We let the Poisson distribution portray the statistical nature of the countings, and chose the region containing the globule Barnard 361 as an example field. Uncertainties due to various combinations of the factors are presented in graphic forms: (1) Dynamic range in the extinction measurements is evaluated as a function of reseau size for varying plate limits. (2) Statistical errors involved in the star-count are analized in terms of the signal-to-noise ratio, the plate limit and the reseau size. (3) Systematic error due to the non-linearity in the number distribution are thoroughly analized. (4) Finally, a methodology is presented for correcting the systematic error in the observed radial density gradient. These graphs are meant to be used in selecting proper size of the reseau and in estimating errors inherent to the star-count analysis.

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Review of the Current Status of the U-238, NP-237 and Th-232 Fission Cross Sections

  • Bak, H.I.;Lorenz, A.
    • Nuclear Engineering and Technology
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    • v.3 no.2
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    • pp.77-97
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    • 1971
  • The experimental fission cross-section data of U-238, Np-237 and Th-232, published up to the end of 1970, are reviewed and analyzed between their respective thresholds and 20.0 MeV. The results of a statistical analysis of the available data, performed with a weighted Least-squares Orthogonal Polynomial Pitting computer programme are presented in the form of point-wise cross-section values together with their uncertainties, and in the form of graphs of the fitted curves with an indication of a region of 95% statistical confidence level. An estimate of the fission spectrum weighted average cross-sections and their respective uncertainties is also given.

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A Study on "Comparing Two Data Sets" as Effective Tasks for the Education of Pre-Service Elementary Teachers (예비초등교사교육을 위한 효과적인 과제로서 "두 자료집합 비교하기" 과제의 가능성 탐색)

  • Tak, Byungjoo;Ko, Eun-Sung;Jee, Young Myon
    • School Mathematics
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    • v.19 no.4
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    • pp.691-712
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    • 2017
  • It is an important to develop teachers' statistical reasoning or thinking by teacher education. In this study, the "comparing two data sets" tasks is focused as a way to develop pre-service elementary teachers' reasoning about core ideas of statistics such as distribution, variability, center, and spread. 6 teams of each 4 pre-service elementary teachers participated on the tasks and their presentations are analyzed based on Pfannkuch's (2006) teachers' inference model in comparing two data sets. As a result, they paid attention to the distribution and variability in the statistical problem solving by the "comparing two data sets" tasks, and used their contextual knowledge to make a statistical decision. In addition, they used some statistics and graphs as the reference for statistical communication, which is expected to provide implications for improving statistical education. The finding implies that the "comparing two data sets" tasks can be used to develop statistical reasoning of pre-service elementary teachers. Some recommendations are suggested for teacher education by these tasks.

The Development of Forest Fire Statistical Management System using Web GIS Technology

  • Jo, Myung-Hee;Kim, Joon-Bum;Kim, Hyun-Sik;Jo, Yun-Won
    • Proceedings of the KSRS Conference
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    • 2002.10a
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    • pp.183-190
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    • 2002
  • In this paper forest fire statistical information management system is constructed on web environment using web based GIS(Geographic Information System) technology. Though this system, general users can easily access forest fire statistical information and obtain them in visual method such as maps, graphs, and text if they have web browsers. Moreover, officials related to forest fire can easily control and manage all information in domestic by accessing input interface, retrieval interface, and out interface. In order to implement this system, IIS 5.0 of Microsoft is used as web server and Oracle 8i and ASP(Active Server Page) are used for database construction and dynamic web page operation, respectively. Also, Arc IMS of ESRI is used to serve map data using Java and HTML as system development language. Through this system, general users can obtain the whole information related to forest fire visually in real time also recognize forest fire prevention. In addition, Forest officials can manage the domestic forest resource and control forest fire dangerous area efficiently and scientifically by analyzing and retrieving huge forest data through this system. So, they can save their manpower, time and cost to collect and manage data.

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vlda: An R package for statistical visualization of multidimensional longitudinal data

  • Lee, Bo-Hui;Ryu, Seongwon;Choi, Yong-Seok
    • Communications for Statistical Applications and Methods
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    • v.28 no.4
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    • pp.369-391
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    • 2021
  • The vlda is an R (R Development Core team et al., 2011) package which provides functions for visualization of multidimensional longitudinal data. In particular, the R package vlda was developed to assist in producing a plot that more effectively expresses changes over time for two different types (long format and wide format) and uses a consistent calling scheme for longitudinal data. The main features of this package allow us to identify the relationship between categories and objects using an indicator matrix with object information, as well as to cluster objects. The R package vlda can be used to understand trends in observations over time in addition to identifying relative relationships at a simple visualization level. It also offers a new interactive implementation to perform additional interpretation, therefore it is useful for longitudinal data visual analysis. Due to the synergistic relationship between the existing VLDA plot and interactive features, the user is empowered by a refined observe the visual aspects of the VLDA plot layout. Furthermore, it allows the projection of supplementary information (supplementary objects and variables) that often occurs in longitudinal data of graphs. In this study, practical examples are provided to highlight the implemented methods of real applications.