http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
- 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
RISS 인기검색어
- 검색키워드
- 저자 : 허순영 (검색결과 130 건)
- 무료
- 기관 내 무료
- 유료
-
-
-
-
허순영 중국어문학연구회 2023 중국어문학논집 Vol.- No.138
The four groups of meteorological texts in the Zhui Geng Lu are based on typhoon, tornado, thunderstorm, snow, tree ice and other meteorological phenomena. These are precious climate observation records for understanding the climate at the end of the Yuan Dynasty. Song and Yuan Dynasty mostly looked for regularity by observing climate change, and tried to explain disaster phenomenon scientifically. As a pure natural science, the five elements are also materials, which also represent meteorological conditions such as wind, rain, thunderstorm and cloud. Meteorology in ancient natural science mainly involved in agriculture and military affairs. Therefore, in the process of analysis, the more we contact with the general understanding of the natural science behind the text at that time, the more we can truly feel the structure of the literary expression of the text.
-
-
Effect of Bias on the Pearson Chi-squared Test for Two Population Homogeneity Test
허순영 조선대학교 기초과학연구원 2012 조선자연과학논문집 Vol.5 No.4
Categorical data collected based on complex sample design is not proper for the standard Pearson multinomial-based chi-squared test because the observations are not independent and identically distributed. This study investigates effects of bias of point estimator of population proportion and its variance estimator to the standard Pearson chi-squared test statistics when the sample is collected based on complex sampling scheme. This study examines the effect under two population homogeneity test. The standard Pearson test statistic can be partitioned into two parts; the first part is the weighted sum of with eigenvalues of design matrix as their weights, and the additional second part which is added due to the biases of the point estimator and its variance estimator. Our empirical analysis shows that even though the bias of point estimator is small, Pearson test statistic is very much inflated due to underestimate the variance of point estimator. In the connection of design-based variance estimator and its design matrix, the bigger the average of eigenvalues of design matrix is, the larger relative size of which the first component part to Pearson test statistic is taking.
-
허순영 조선대학교 기초과학연구원 2014 조선자연과학논문집 Vol.7 No.3
National-wide and/or large scale sample surveys generally use complex sample design. Traditional Pearson chi-square test isnot appropriate for the categorical complex sample data. Rao-Scott suggested an adjustment method for Pearson chi-square test,which uses the average of eigenvalues of design matrix of cell probabilities. This study is to compare the efficiency of Rao-Scottfirst order adjusted test to Wald test for homogeneity between two populations using 2009 Gyeongnam regional educationoffices's customer satisfaction survey (2009 GREOCSS) data. The 2009 GREOCSS data were collected based on stratifiedthree-stage cluster sampling with probability proportional to size. The empirical results show that the Rao-Scott adjusted teststatistic using only the variances of cell probabilities is very close to the Wald test statistic, which uses the covariance matrix ofcell probabilities, under the 2009 GREOCSS data based. However it is necessary to be cautious to use the Rao-Scott first orderadjusted test statistic in the place of Wald test because its efficiency is decreasing as the relative variance of eigenvalues of thedesign matrix of cell probabilities is increasing, specially more when the number of degrees of freedom is small.
-
Linear Measurement Error Variance Estimation based on the Complex Sample Survey Data
허순영,장덕준 조선대학교 기초과학연구원 2012 조선자연과학논문집 Vol.5 No.3
Measurement error is one of main source of error in survey. It is generally defined as the difference between an observed value and an underlying true value. An observed value with error may be expressed as a function of the true value plus error term. In some cases, the measurement error variance may be also a function of the unknown true value. The error variance function can be rewritten as a function of true value multiplied by a scale factor. This research explore methods for estimation of the measurement error variance based on the data from complex sampling design. We consider the case in which the variance of mesurement error is a linear function of unknown true value, and the error variance scale factor is small. We applied our results to the U.S. Third National Health and Nutrition Examination Survey (the U.S. NHANES Ⅲ) data for empirical analyses, which has replicate measurements for relatively small subset of initial respondents's group.
-
-
ScienceON연관 검색어 추천
이 검색어로 많이 본 자료
활용도 높은 자료
