• Communications for Statistical Applications and Methods
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• v.16 no.5
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• pp.763-779
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• 2009

Sample design is studied to estimate the number of records from singing rooms. The definition of survey population, stratification, sample size and allocation of sample are discussed with using the collected real data. The validity of sample design is testified by the log data collected from online singing room which is sampled with suggested design. Estimation of the number of hitting of off-line singing room is proposed and calculated from the log data collected from sampled off-line singing rooms. The difference of online and off-line singing rooms is analyzed and the method of distribution of singing room royalty is suggested.

• Communications for Statistical Applications and Methods
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• v.4 no.1
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• pp.151-159
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• 1997

In sample surveys, we expect preferred samples that reduce the survey cost and increase the precision of estimators will be selected. Goodman and Kish (1950) introduced controlled selection as a method of sample selection that increases the probability of drawing preferred samples, while decreases the probability of drawing nonpreferred samples. In this paper, we obtain the controlled plans using the maximum entropy principle, and when the order of nonpreferred samples is considered, we propose the algorithm to obtain a controlled plan.

• The Korean Journal of Applied Statistics
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• v.8 no.2
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• pp.43-54
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• 1995

The fishery household economy survey is a sample survey which produce estimates on the fishery household economy and fishery management in Korea. We propose a sample design for this survey. This design is developed based on results of 1990 fishery census and Shi-Do is assumed to be subpopulation for Shi-Do estimates. Samples are selected by stratified two-stage cluster sampling in Shi-Do and income function is found for stratification. Fishery household income is estimated by a linear estimator.

• The Korean Journal of Applied Statistics
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• v.4 no.1
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• pp.65-83
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• 1991

In order to know the situation of statistical Quality Control in Korea, we have surveyedabout 4, 500 manufacturing companies in Korea. Among the first 4, 500 manufacturing companies, 2, 586 companies have answered for the questionairs of the sample survey. In this research a statistical analysis is conducted for the 2, 586 companies and diagnosis of the situation of Statistical Quality Control is Korea in presented in terms of levels of development and degrees of implementation.

• The Korean Journal of Applied Statistics
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• v.4 no.2
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• pp.137-148
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• 1991

This paper describes the design of sample of the survey on the trend of house prices in city areas. The purpose of this research is to increase the precision of house price index in 39 cities and to provide with an accurate house price indes. The sample is selected in the stratified two stage sampling. In chapter 2, review and discussions are given on the sample design now in use. In chapter 3, we describe the sample size and the stratification, the house price index and error, and the substitution of sample. Finally we consider on problems of the sample design and some alternatives to solve them.

• The Korean Journal of Applied Statistics
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• v.18 no.1
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• pp.27-41
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• 2005

We made a new sample design for intestinal parasitic infection survey in 2004. We used the 10% sample survey data of 2000 population and housing census as a survey population. Since the infection rates of intestinal parasitics are very low, we applied the relative risk and odds ratio instead of ordinary method such as t-test to study the characteristics from the 1997 survey data. In order to allocate samples to stratum, we used the compromise of Neyman allocation which is the average of three Neyman allocations. And also, we derive estimators and variance estimators of the estimators.

• Communications for Statistical Applications and Methods
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• v.12 no.1
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• pp.29-38
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• 2005

In sample design, determining the weights of estimates becomes usually great influence on the result. In this article, raking methods are applied to different domain and depending on the range of the domain and sample size, the results of estimates are explained and compared. For the comparison, we use the MSE, MAE, MSPE and MAPE with Actual State of Minor Enterprisers Human Resources Survey data in 2001. The simulation result shows that more elaborate method is superior to the widely used method as expected but the difference is not quite significant.

• Communications for Statistical Applications and Methods
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• v.9 no.2
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• pp.565-576
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• 2002

We propose a new sampling design for the 2001 Health Index Survey at Seoul. In this stratified two-stage sampling design, the ED(enumeration district) of 2000 Population and Housing Census is used as primary sampling unit and the Gu is used as stratification variable in order to obtain the sub-domain estimate for 25 Gu's as well as population estimate for Seoul. The sample ED's are systematically selected after the Ed's are ordered by location and property to obtain a representative sample. And also, the imputation methods for item nonresponses are suggested.

• The Korean Journal of Applied Statistics
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• v.32 no.4
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• pp.643-652
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• 2019

We propose a method for sample size determination using design effect formulas when a sample is resigned for a repeated survey. The proposed method enables the determination of the sample size by incorporating the impact of various design components to the sampling error through design effect formulas that are applicable under multistage sampling design and stratified multistage sampling designs.

• The Korean Journal of Applied Statistics
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• v.24 no.2
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• pp.393-400
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• 2011

In a large scale survey, cluster sampling design in which a set of observation units called clusters are selected is often used to satisfy practical restrictions on time and cost. Especially, a two stage cluster sampling design is preferred when a strong intra-class correlation exists among observation units. The sample Primary Sampling Unit(PSU) and Secondary Sampling Unit(SSU) size for a two stage cluster sample is determined by the survey cost and precision of the estimator calculated. For this study, we derive the optimal sample PSU and SSU size when the population SSU size across the PSU are di erent by extending the result obtained under the assumption that all PSU have the same number of SSU. The results on the sample size are then applied to the $4^{th}$ Korea Hospital Discharge results and is compared to the conventional method. We also propose the optimal sample SSU (discharged patients) size for the $7^{th}$ Korea Hospital Discharge Survey.