• Title/Summary/Keyword: dependent variable

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A Study of Vlog that Analyze Variables Affecting Perceived Enjoyment : Using Social Communication as a Control Variable

  • Yu, Giseob;Lim, Jeong Hun;Cho, Namjae
    • Journal of Information Technology Applications and Management
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    • v.27 no.5
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    • pp.23-33
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    • 2020
  • As the 4G and 5G Internet technologies become more common and developed, an environment for uploading and watching videos is created and spread, in addition to simply uploading posts. Watching and sharing daily life among media contents called Vlog, are very common more than ever. This means that individual users could access Vlog easily and the situation could be new trend. Additionally, academic research about Volg is increasing. We analyzed three independent variables affecting a perceived enjoyment we set up the dependent variable. Information search, self-expression, and social need are set as independent variables and social interaction is set as the control variable. Information search and self-expression are significant effect to perceived enjoyment except social need. In particular, social interaction as a control variable has effect to all relationships.

A Case Study On the 6th Graders' Understanding of Variables Using LOGO Programming (Logo 프로그래밍을 통한 초등학교 6학년 아동의 변수개념 이해)

  • 류희찬;신혜진
    • Journal of Educational Research in Mathematics
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    • v.10 no.1
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    • pp.85-102
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    • 2000
  • The concept of variables is central to mathematics teaching and learning in junior and senior high school. Understanding the concept provides the basis for the transition from arithmetic to algebra and necessary for the meaningful use of all advanced mathematics. Despite the importance of the concept, however, much has been written in the last decade concerning students' difficulties with the concept. This Thesis is based on research to investigate the hypothesis that LOGO programming will contribute to 6th grader' learning of variables. The aim of the research were to; .investigate practice on pupils' understanding of variables before the activity with a computer; .identify functions of LOGO programming in pupils' using and understanding of variable symbols, variable domain and the relationship between two variable dependent expressions during the activity using a computer; .investigate the influence of pupils' mathematical belief on understanding and using variables. The research consisted predominantly of a case study of 6 pupils' discourse and activities concerning variable during their abnormal lessons and interviews with researcher. The data collected for this study included video recordings of the pupils'work with their spoken language.

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Nonparametric kernel calibration and interval estimation (비모수적 커널교정과 구간추정)

  • 이재창;전명식;김대학
    • The Korean Journal of Applied Statistics
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    • v.6 no.2
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    • pp.227-235
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    • 1993
  • Calibration relates the estimation of independent variable which rquires more effort or expense than dependent variable does. It would be provided with high accuracy because a little change of the result of independent variable cn cause a serious effect to the human being. Usual statistical analysis assumes the normality of error distribution or linearity of data. It is desirable to analyze the data without those assumptions for the accuracy of the calibration. In this paper, we calibrated the data nonparametrically without those assumptions and derived confidence interval estimate for the independent variable. As a method, we used kernel method which is popular in modern statistical branch. We derived bootstrap confidence interval estimate from the bootstrap confidence band.

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CHAID Algorithm by Cube-based Sampling

  • Park, Hee-Chang;Cho, Kwang-Hyun
    • 한국데이터정보과학회:학술대회논문집
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    • 2003.10a
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    • pp.239-247
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    • 2003
  • Decision tree algorithms are used extensively for data mining in many domains such as retail target marketing, fraud dection, data reduction and variable screening, etc. CHAID(Chi-square Automatic Interaction Detector), is an exploratory method used to study the relationship between a dependent variable and a series of predictor variables. In this paper we propose and CHAID algorithm by cube-based sampling and explore CHAID algorithm in view of accuracy and speed by the number of variables.

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A compound Poisson risk model with variable premium rate

  • Song, Mi Jung;Kim, Jongwoo;Lee, Jiyeon
    • Journal of the Korean Data and Information Science Society
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    • v.23 no.6
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    • pp.1289-1297
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    • 2012
  • We consider a general compound Poisson risk model in which the premium rate is surplus dependent. We analyze the joint distribution of the surplus immediately before ruin, the deffcit at ruin and the time of ruin by solving the integro-differential equation for the Gerber-Shiu discounted penalty function.

Variable Selection Based on Mutual Information

  • Huh, Moon-Y.;Choi, Byong-Su
    • Communications for Statistical Applications and Methods
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    • v.16 no.1
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    • pp.143-155
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    • 2009
  • Best subset selection procedure based on mutual information (MI) between a set of explanatory variables and a dependent class variable is suggested. Derivation of multivariate MI is based on normal mixtures. Several types of normal mixtures are proposed. Also a best subset selection algorithm is proposed. Four real data sets are employed to demonstrate the efficiency of the proposals.

Estimation on Modified Proportional Hazards Model

  • Lee, Kwang-Ho;Lee, Mi-Sook
    • Journal of the Korean Data and Information Science Society
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    • v.5 no.1
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    • pp.59-66
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    • 1994
  • Heller and Simonoff(1990) compared several methods of estimating the regression coefficient in a modified proportional hazards model, when the response variable is subject to censoring. We give another method of estimating the parameters in the model which also allows the dependent variable to be censored and the error distribution to be unspecified. The proposed method differs from that of Miller(1976) and that of Buckely and James(1979). We also obtain the variance estimator of the coefficient estimator and compare that with the Buckely-James Variance estimator studied by Hillis(1993).

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A DISCONTINUOUS GALERKIN METHOD FOR A MODEL OF POPULATION DYNAMICS

  • Kim, Mi-Young;Yin, Y.X.
    • Communications of the Korean Mathematical Society
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    • v.18 no.4
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    • pp.767-779
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    • 2003
  • We consider a model of population dynamics whose mortality function is unbounded. We approximate the solution of the model using a discontinuous Galerkin finite element for the age variable and a backward Euler for the time variable. We present several numerical examples. It is experimentally shown that the scheme converges at the rate of $h^{3/2}$ in the case of piecewise linear polynomial space.

The Time Correlation Function Near (and at) a Stable Steady State, When a Chemical System Relaxes from the Unstable Steady State$^*$

  • Lee, Dong-Jae;Ryu, Moon-Hee;Lee, Jong-Myung
    • Bulletin of the Korean Chemical Society
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    • v.6 no.2
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    • pp.91-95
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    • 1985
  • The dynamic properties near (and at) a stable steady state are discussed, when a chemical system relaxes from the unstable steady state. The time-dependent correlation length for the fluctuating variable near a stable steady state is explicitly obtained by introducing the probability average for the variable satisfying the rate equation. The study is carried out about the effect of nonlinearity on the correlation length near (and at) a stable steady state.

Estimation of the electricity demand function using a lagged dependent variable model (내생시차변수모형을 이용한 전력수요함수 추정)

  • Ahn, So-Yeon;Jin, Se-Jun;Yoo, Seung-Hoon
    • Journal of Energy Engineering
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    • v.25 no.2
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    • pp.37-44
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    • 2016
  • The demand for electricity has a considerable impact on various energy sectors since electricity is generated from various energy sources. This paper attempts to estimate the electricity demand function and obtain some quantitative information on price and income elasticities of the demand. To this end, we apply a lagged dependent variable model to derive long-run as well as short-run elasticities using the time-series data over the period 1991-2014. Our dependent variable is annual electricity demand. The independent variables include constant term, real price of electricity, and real gross domestic product. The results show that the short-run price and income elasticities of the electricity demand are estimated to be -0.142 and 0.866, respectively. They are statistically significant at the 5% level. That is, the electricity demand is in-elastic with respect to price and income changes in the short-run. The long-run price and income elasticities of the electricity demand are calculated to be -0.210 and 1.287, respectively, which are also statistically meaningful at the 5% level. The electricity demand is still in-elastic with regard to price change in the long-run. However, the electricity demand is elastic regarding income change in the long-run. Therefore, this indicates that the effect of demand-side management policy through price-control is restrictive in both the short- and long-run. The growth in electricity demand following income growth is expected to be more remarkable in the long-run than in the short-run.