• Title/Summary/Keyword: statistics

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A STUDY ON THE STIMULATIONOF INTEREST IN LEARNING STATISTICS THROUGH SPREADSHEET (엑셀을 활용한 통계 수업의 흥미도 신장 방안)

  • 김동제;박용범
    • School Mathematics
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    • v.3 no.1
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    • pp.109-129
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    • 2001
  • The concern of this paper is to provide learning opportunities to participate in the class of statistics with interest for the students who dislike mathematics and especially find difficulty in understanding statistics. The students were encouraged to arrange data collected in their daily life by the use of spreadsheet program and to interpret the result of data with graphs, so that they could have a great interest in statistics and make steady progress in their voluntary study. The further study to use computers in teaching mathematics should be continued and recommended in the rapid age of information and knowledge-based.

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A Test for Independence between Two Infinite Order Autoregressive Processes

  • Kim, Eun-Hee;Lee, Sang-Yeol
    • Proceedings of the Korean Statistical Society Conference
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    • 2003.05a
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    • pp.191-197
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    • 2003
  • This paper considers the independence test for two stationary infinite order autoregressive processes. For a test, we follow the empirical process method devised by Hoeffding (1948) and Blum, Kiefer and Rosenblatt (1961), and construct the Cram${\acute{e}}$r-von Mises type test statistics based on the least squares residuals. It is shown that the proposed test statistics behave asymptotically the same as those based on true errors.

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BOOTSTRAPPING GENERALIZED LINEAR MODELS WITH RANDOM REGRESSORS

  • Lee, Kee-Won;Kim, Choong-Rak;Sohn, Keon-Tae;Jeong, Kwang-Mo
    • Journal of the Korean Statistical Society
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    • v.21 no.1
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    • pp.70-79
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    • 1992
  • The generalized linear models with random regrssors case are studied for bootstrapping. Only the natural link functions are considered. It is shown that the bootstrap approximation to the distribution of the maximum likelihood estimators is valid for almost all sample sequences. A slight extension of this model is also considered.

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Identification of Multiple Outlying Cells in Multi-way Tables

  • Lee, Jong Cheol;Hong, Chong Sun
    • Communications for Statistical Applications and Methods
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    • v.7 no.3
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    • pp.687-698
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    • 2000
  • An identification method is proposed in order to detect more than one outlying cells in multi-way contingency tables. The iterative proportional fitting method is applied to get expected values of several suspected outlying cells. Since the proposed method uses minimal sufficient statistics under quasi log-linear models, expected counts of outlying cells could be estimated under any hierarchical log-linear models. This method is an extension of the backwards-stepping method of Simonoff(1988) and requires les iteration to identify outlying cells.

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A Family of Tests for Trend Change in Mean Residual Life with Known Change Point

  • Na, Myung-Hwan;Kim, Jae-Joo
    • Communications for Statistical Applications and Methods
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    • v.7 no.3
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    • pp.789-798
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    • 2000
  • The mean residual function is the expected remaining life of an item at age x. The problem of trend change in the mean residual life is great interest in the reliability and survival analysis. In this paper, we develop a family of test statistics for testing whether or not the mean residual life changes its trend. The asymptotic normality of the test statistics is established. Monte Carlo simulations are conducted to study the performance of our test statistics.

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A Multiple Unit Roots Test Based on Least Squares Estimator

  • Shin, Key-Il
    • Journal of the Korean Statistical Society
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    • v.28 no.1
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    • pp.45-55
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    • 1999
  • Knowing the number of unit roots is important in the analysis of k-dimensional multivariate autoregressive process. In this paper we suggest simple multiple unit roots test statistics based on least squares estimator for the multivariate AR(1) process in which some eigenvalues are one and the rest are less than one in magnitude. The empirical distributions are tabulated for suggested test statistics. We have small Monte-Calro studies to compare the powers of the test statistics suggested by Johansen(1988) and in this paper.

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Procedures for Detecting Multiple Outliers in Linear Regression Using R

  • Kwon, Soon-Sun;Lee, Gwi-Hyun;Park, Sung-Hyun
    • Proceedings of the Korean Statistical Society Conference
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    • 2005.11a
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    • pp.13-17
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    • 2005
  • In recent years, many people use R as a statistics system. R is frequently updated by many R project teams. We are interested in the method of multiple outlier detection and know that R is not supplied the method of multiple outlier detection. In this talk, we review these procedures for detecting multiple outliers and provide more efficient procedures combined with direct methods and indirect methods using R.

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Testing for A Change Point by Model Selection Tools in Linear Regression Models

  • Yoon, Yong-Hwa;Kim, Jong-Tae;Cho, Kil-Ho;Shin, Kyung-A
    • Communications for Statistical Applications and Methods
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    • v.7 no.3
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    • pp.655-665
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    • 2000
  • Several information criterions, Schwarz information criterion (SIC), Akaike information criterion (AIC), and the modified Akaike information criterion ($AIC_c$), are proposed to locate a change point in the multiple linear regression model. These methods are applied to a stock Exchange data set and compared to the results.

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DIRECTIONAL LOG-DENSITY ESTIMATION

  • Huh, Jib;Kim, Peter T.;Koo, Ja-Yong;Park, Jin-Ho
    • Journal of the Korean Statistical Society
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    • v.33 no.3
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    • pp.255-269
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    • 2004
  • This paper develops log-density estimation for directional data. The methodology is to use expansions with respect to spherical harmonics followed by estimating the unknown parameters by maximum likelihood. Minimax rates of convergence in terms of the Kullback-Leibler information divergence are obtained.