• Bulletin of the Korean Mathematical Society
• /
• v.51 no.3
• /
• pp.701-716
• /
• 2014

The limiting distribution for the linear placement statistics under the null hypotheses has been provided by Orban and Wolfe [9] and Kim [5] when one of the sample sizes goes to infinity, and by Kim, Lee and Wang [6] when the sample sizes of each group go to infinity simultaneously. In this paper we establish the generalized Kruskal-Wallis one-way analysis of variance for the linear placement statistics.

• Journal of the Korea Construction Safety Engineering Association
• /
• s.43
• /
• pp.98-106
• /
• 2007

In this paper, a ground disturbance effects, strength and consolidation characteristics of soft clay through using the large block samples($\theta$:300mm, H:400mm) and the piston samples, f hose which had been gathered in west coast and south coast. Especially, we have assessed the coefficient of horizontal consolidation when penetrating the mandrel considering the variance of ratio between diameter and height in drainage sample through the experiment of the oedometer test and Rowecell and also investigated the disturbance area in smear zone by interior model test, the strength originated by disturbance, the variance in characteristics of the consolidation. As the result, the large block sample has been investigated that ihe uniaxial compression test(qu) was shown bigger than the piston sample by about 11-19%. Under the size of anistropy in consolidation, the coefficient ratio of consolidation(ch/cv,) perfomed by standard consolidation test(SC) was shown bigger than that of (Cro/Cv) by the Rowecell test. And the coefficient ratio of consolidation(Cro/Cv) perfomed by piston sample was evaluated bigger than that Of (Cro/Cv) by the large block sample by about 0.9-1.9. The coefficient ratio of consolidation along with the variance in ratio of between diameter and height when penetrating the mandrel was shown big difference according to the characteristics of soil of the specimen. In addition, ds/dw of smear zone at the marine clay in west-south was ranged from 1.6 to 4.2. The width of variance in rat io[(qud)/(quud)] of strength n the area between disturbance and undisturbance was shown big as about 72-91% but the principle was judged with the similiar range when the decrease of the strength in smear zone become the zone under 25% in unditurbance area.

• Journal of the Korean Data and Information Science Society
• /
• v.1
• /
• pp.59-65
• /
• 1990

The Edgeworth expansion, the Roy-Tiku method and the bootstrap method for approximating the distribution of the sample variance are compared through the Monte Carlo simulation study.

• Proceedings of the Korean Association for Survey Research Conference
• /
• 2001.04a
• /
• pp.59-71
• /
• 2001

We investigate design-based variance estimation methods of homogeneous linear estimator for population total under stratified multi-stage sampling. One method is unbiasedly estimating the first stage variance and the second stage variance separately in each stratum. And another is sub-sampling method that estimating the first stage variance only by using sub-sample selected from the second stage sample so that resulting estimator is unbiased for the total variance. The first is useful when the second stage unbiased estimator is available and the second is when the second stage variance is not estimable. For each case, we proposed a form of non-negative unbiased variance estimator. We expect the proposed variance estimation methods can be effectively used for many practical surveys.

• Survey Research
• /
• v.2 no.1
• /
• pp.59-71
• /
• 2001

We investigate design-based variance estimation methods of homogeneous linear estimator for population total under stratified multi-stage sampling. One method is unbiasedly estimating the first stage variance and the second stage variance separately in each stratum. And another is sub-sampling method that estimating the first stage variance only by using sub-sample selected from the second stage sample so that resulting estimator is unbiased for the total variance. The first is useful when the second stage unbiased estimator is available and the second is when the second stage variance is not estimable. For each case, we proposed a form of non-negative unbiased variance estimator. We expect the proposed variance estimation methods can be effectively used for many practical surveys.

• The Korean Journal of Applied Statistics
• /
• v.14 no.1
• /
• pp.13-24
• /
• 2001

In this paper, we investigated mean estimation methods in two-phase sampling. Under the fixed expected cost we reviewed the optimal sample sizes, minimum variances and approximate unbiased variance estimators for usual ratio estimator, stratified sample mean with proportional allocation and Rao's allocation of the second phase sample. Also we proposed combined ratio estimator, which uses both ratio estimation and stratification and derived optimal sample size, minimum variance and unbiased variance estimator. Through a limited simulation study, we compared estimators by design effects and came to know that ratio estimator is more efficient than stratified sample mean in some cases and inefficient in the other cases, but combined ratio estimator is more efficient than others in most cases.

• The Mathematical Education
• /
• v.45 no.2 s.113
• /
• pp.145-154
• /
• 2006

The main purpose of this study is to investigate the effect of departures from normality and equal variance on the two-sample test when the variances are unknown. We have found that type I error brought about a little bit change which is ignorable in relation to kurtosis. But the change of type I error was mainly based on the skewness of the parent population. In introductory statistics classes where data analysis includes techniques for detecting skewness of two populations, we recommend the two-sample t-test when maximal skewness of two populations is smalter than the value 4 when the variances seem equal. Furthermore, our simulations reveal that the two-sample t-test appears somewhat more robust than that of z-test if the assumption of equal variance is satisfied. In the case of unequal variance, the two-sample t-test appears somewhat more robust provided the t-statistic using Satterthwaite's approximate degrees of freedom.

• Journal of Animal Science and Technology
• /
• v.55 no.2
• /
• pp.103-107
• /
• 2013

A crucial first step in the planning of any scientific experiment is to evaluate an appropriate sample size to permit sufficient statistical power to detect the desired effect. In this study, we investigated the optimal sample size of quantitative trait locus (QTL) linkage analysis for simple random sibship samples in pedigreed chicken populations, under the variance component framework implemented in the genetic power calculator program. Using the program, we could compute the statistical power required to achieve given sample sizes in variance component linkage analysis in random sibship data. For simplicity, an additive model was taken into account. Power calculations were performed to relate sample size to heritability attributable to a QTL. Under the various assumptions, comparative power curves indicated that the power to detect QTL with the variance component method is highly affected by a function of the effect size of QTL. Hence, more power can be achievable for QTL with a larger effect. In addition, a marked improvement in power could be obtained by increasing the sibship size. Thus, the use of chickens is advantageous regarding the sampling unit issue, since desirable sibship size can be easily obtained compared with other domestic species.

• Communications for Statistical Applications and Methods
• /
• v.20 no.4
• /
• pp.247-257
• /
• 2013

A variety of practical problems can be addressed in the framework of rotation (successive) sampling. The present work presents a sample rotation pattern where sampling units are drawn on two successive occasions. The problem of estimation of population variance on current (second) occasion in two - occasion successive (rotation) sampling has been considered. A class of estimators has been proposed for population variance that includes many estimators as a particular case. Asymptotic properties of the proposed class of estimators are discussed. The proposed class of estimators is compared with the sample variance estimator when there is no matching from the previous occasion. Optimum replacement policy is discussed. Results are supported with the empirical means of comparison.

• Journal of the Korean Data and Information Science Society
• /
• v.28 no.2
• /
• pp.443-449
• /
• 2017

Estimation of population proportion like the distribution rate of LED TV and the prevalence of a disease are often estimated based on survey sample data. Population proportion is generally considered as a special form of population mean. In complex sampling like stratified multistage sampling with unequal probability sampling, the denominator of mean may be random variable and it is estimated like ratio estimator. In this research, we examined the estimation of distribution rate based on stratified multistage sampling, and determined some numerical outcomes using stratified random sample data with about 25% of missing observations. In the data used for this research, the survey weight was determined by deterministic way. So, the weights are not random variable, and the population distribution rate and its variance estimator can be estimated like population mean estimation. When the weights are not random variable, if one estimates the variance of proportion estimator using ratio method, then the variances may be inflated. Therefore, in estimating variance for population proportion, we need to examine the structure of data and survey design before making any decision for estimation methods.