• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.32 no.1
• /
• pp.26-38
• /
• 2020

A statistical test was carried out on the IID (Independently and Identically Distributed) assumption of the AM (Annual Maxima) data used to estimate the design wave height. The test was divided into independence (randomness) test and homogeneity test, and each test was conducted on AM data of 210 and 310 stations in coastal and inner coastal grids in typhoon and non-typhoon (monsoon) conditions. As a result of the independence test, the rejection ratios of the test are in the range of 1.8~5.3% and 1.4~6.0% for the non-typhoon and typhoon data sets, respectively. On the other hand, in the distribution difference test of typhoon data and nontyphoon data, the same distribution hypothesis was found to be rejected in the range of 47~79% according to the test method for both coastal grid and inner coastal grid. Therefore, in estimating design wave height by extreme value analysis, the estimation process by dividing the typhoon and non-typhoon data is appropriate.

• Journal of Korea Multimedia Society
• /
• v.14 no.10
• /
• pp.1243-1251
• /
• 2011

This paper proposes a new vehicle model recognition using scale invariant feature transform to car's headlights image. Proposed vehicle model recognition raises the accuracy using "homogeneity" calculated from the distribution of features. In the experiment with 400 test images taken from 54 different vehicles, proposed method has 90% recognition rate and 16.45 homogeneity.

• Communications for Statistical Applications and Methods
• /
• v.16 no.2
• /
• pp.389-396
• /
• 2009

Approximations for the null distribution of a test statistic arising in multivariate analysis to test homogeneity of variances and a mixture of two beta distributions by making use of a product of beta baseline density function and a polynomial adjustment, so called beta-polynomial density approximant, are discussed. Explicit representations of density and distribution approximants of interest in each case can easily be obtained. Beta-polynomial density approximants produce good approximation over the entire range of the test statistic and also accommodate even the bimodal distribution using an artificial example of a mixture of two beta distributions.

• Journal of Soil and Groundwater Environment
• /
• v.18 no.5
• /
• pp.15-25
• /
• 2013

In this study, two kinds of soil-based proficiency testing materials (PTMs), NICE-012L and NICE-012R were prepared and certified for Benzen, Toluene, Etylbenzene and Xylene with evaluation of uncertainties. In order to analyse BTEX (Benzen Toluene Etylbenzene Xylene) for the candidate materials, GC/MS was used after pretreatment according to methods of soil analysis by Ministry of Environment. For the homogeneity test among bottles in terms of candidate materials, ISO 13528 and IUPAC Protocol were used and according to the result, both candidate materials showed sufficient homogeneity. Also, the stability test over the candidate materials was accessed according to the ISO Guide 35 by classifying short-term and long-term stability and the result showed that both candidate materials showed decent stability. The reference values of the two candidate materials depending on BTEX components were derived from the average of the 11 samples that were used for verification of the samples' homogeneity. Uncertainty of measurement was combined by uchar that was caused by a characteristic value, $u_{bb}$ that was caused by between-bottle homogeneity, and $u_{stab}$ that was caused by stability, and then combined uncertainty ($u_{PTM}$) was multiplied to the coverage factor (k) derived from the effective degree of freedom from each factor that leads to expanded uncertainty (U) in about 95% of confidence level. The proficiency testing materials developed through this study were supplied to National Institute of Environmental Research (NIER) and utilized as an external proficiency testing materials for evaluating analysis capacity of soil agencies with specialty in terms of soil analysis approved by Minister of Environment.

• Journal of Integrative Natural Science
• /
• v.12 no.3
• /
• pp.91-99
• /
• 2019

Many researchers in various study fields use the two sample t-test to confirm their treatment effects. The two sample t-test is generally used for small samples, and assumes that two independent random samples are selected from normal populations, and the population variances are unknown. Researchers often conduct F-test, the test of equality of variances, before testing the treatment effects, and the test statistic or confidence interval for the two sample t-test has two formats according to whether the variances are equal or not. Researchers using the two sample t-test often want to know how large sample sizes they need to get reliable test results. This research gives some guidelines for sample sizes to them through simulation works. The simulation had run for normal populations with the different ratios of two variances for different sample sizes (${\leq}30$). The simulation results are as follows. First, if one has no idea equality of variances but he/she can assume the difference is moderate, it is safe to use sample size at least 20 in terms of the nominal level of significance. Second, the power of F-test for the equality of variances is very low when the sample sizes are small (<30) even though the ratio of two variances is equal to 2. Third, the sample sizes at least 10 for the two sample t-test are recommendable in terms of the nominal level of significance and the error limit.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.18 no.4
• /
• pp.107-117
• /
• 2014

This study tests homogeneity and performs multiple comparison analysis among treatment levels of each factor group through t-test by materials and analysis of variance by structural type and service period. For that descriptive statistical analysis is performed for static and dynamic response characteristics and their ratios of calculated versus measured values based on a good many safety assessment reports for bridges. Homogeneity and post hoc test based on descriptive statistical analysis provide the measures for homogeneity identification among comparison groups in addition to the statistical reference values such as central tendency, variation and shape. This study is expected to be valuable for structural integrity assessment and design by comparing the measured and calculated values with the reference values for the homogeneous group identified, which can help the engineers review the adequacy of the values and put the group database to practical use.

• Journal of Korean Society for Quality Management
• /
• v.45 no.3
• /
• pp.447-462
• /
• 2017

Purpose: This study aims to develop distributable samples that can be used for proficiency testing to verify the ability of the testing laboratory to perform high temperature and low temperature tests. Method: In this study, the temperature-resistance characteristics of the NTC thermistor were used to develop samples. The homogeneity and stability of samples were examined according to the proficiency testing requirements. Results: Thirty samples with homogeneity and stability were developed and used for the proficiency testing. Thus, it was possible to distinguish between the test laboratories that showed satisfactory results and those that did not. Conclusion: It was the first time to develop samples that can be used for proficiency testing in high temperature and low temperature tests. and it was proved that the proficiency test program can be operated using the characteristics of NTC thermistor.

• Journal of the Korean Society of Hazard Mitigation
• /
• v.9 no.4
• /
• pp.29-35
• /
• 2009

In this study, quantitative homogeneity analysis was performed between rainfall observation data set of Chukwooki(CWK) and rainfall observation data set of modern rain gage(MRG) using statistical methods such as basic statistics, K-S test and Boxplots. To analyze the homogeneities of CWK and MRG four rainfall characteristic series such as monthly rainfall, the ratio of maximum daily rainfall to monthly rainfall, number of rainy days for each month, and the ratio of monthly rainfall to numbers of rainy days are made, and the homogeneity tests using two sample K-S test and quantitative comparisons were performed. The test results showed that observation precisions between CWK and MRG of original data set(M00) were differed because M00 clearly showed the statistical significances on differences of numbers of monthly rainy days of CWK and MRG. But, rainfall showed a little differences which were not significant between CWK and MRG.

• Journal of Integrative Natural Science
• /
• v.5 no.4
• /
• pp.241-245
• /
• 2012

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 ${\chi}^2_1$ 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.

• Journal of Integrative Natural Science
• /
• v.7 no.3
• /
• pp.208-213
• /
• 2014

National-wide and/or large scale sample surveys generally use complex sample design. Traditional Pearson chi-square test is not 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-Scott first order adjusted test to Wald test for homogeneity between two populations using 2009 Gyeongnam regional education offices's customer satisfaction survey (2009 GREOCSS) data. The 2009 GREOCSS data were collected based on stratified three-stage cluster sampling with probability proportional to size. The empirical results show that the Rao-Scott adjusted test statistic using only the variances of cell probabilities is very close to the Wald test statistic, which uses the covariance matrix of cell probabilities, under the 2009 GREOCSS data based. However it is necessary to be cautious to use the Rao-Scott first order adjusted test statistic in the place of Wald test because its efficiency is decreasing as the relative variance of eigenvalues of the design matrix of cell probabilities is increasing, specially more when the number of degrees of freedom is small.