• Education of Primary School Mathematics
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• v.22 no.4
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• pp.205-221
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• 2019

The study aimed at investigating preservice elementary school teachers' statistical reasoning when they posed survey questions as they engaged in statistical problem solving, and analyzing how their statistical reasoning affect the subsequent stages. 24 groups of sophomore students(80 students) from two education universities conducted statistical problem solving and completed statistical report, and 22 of them were analyzed. As a result, 9 statistical reasoning were shown when preservice teachers posed survey questions. Among them, question clarification oriented reasoning and variability based reasoning were not exclusively focused upon in the previous research. In order to investigate how statistical reasoning in posing survey questions affected subsequent stages, we examined difficulties and issues that preservice teachers had when they engaged in analyses and conclusion stage described in their report. Consequently, preservice teachers' difficulties were related to population relevant reasoning, category level reasoning, standardization reasoning, alignment to question reasoning, and question clarification oriented reasoning. While previous studies did not focus on question posing stage, this study claimed the necessity of emphasizing various statistical reasoning in question posing and importance of teaching and learning method of appropriate statistical reasoning in question posing.

• Communications for Statistical Applications and Methods
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• v.8 no.3
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• pp.753-765
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• 2001

We suggest a quantitative conditional unrelated question model that can be used in obtaining more sensitive information. For whom say "yes" about the less 7han sensitive question .B we ask only about the more sensitive variable X. We extend our model to two sample case when there is no information about the true mean of the unrelated variable Y. Finally we compare the efficiency of our model with that of Greenberg et al.′s.

• Journal of the Korean Statistical Society
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• v.5 no.1
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• pp.35-48
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• 1976

Since the solution vector for input-output forecasting models is not directly obtainable, several iterative procedures have been proposed and utilized. As is often the case in numerical analysis, the question of the consistency between the original system and the converged system of the proposed iteration has been ignored, and no one has tried to express the converged solution explicitly. This paper examines this question and points out the inconsistencies between various well-known iterative procedures used to solve input-output models and the original input-output system.

• Communications for Statistical Applications and Methods
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• v.13 no.2
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• pp.319-326
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• 2006

Randomized response technique is a survey technique for eliminating evasive answer bias. This technique is popular in social survey for sensitive issues. In this paper we present a simple and obvious procedure for estimating the population proportion of a sensitive group. Here, we shows the weak point in the method of Kim and Warde (2005). Also, it is found that the proposed procedure is more efficient than the ones of Warner (1965) and Kim and Warde (2005). Lastly we discuss the conditions that the suggested method will be more efficienct.

• The Korean Journal of Applied Statistics
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• v.13 no.2
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• pp.575-590
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• 2000

In this paper, we extended the Kim et al.'s two-stage unrelated question model(1992) and the Lee et al.'s improved unrelated question model(1998) to two sample unrelated question model of using two independent samples in the case of unknown $\pi_y$.

• Communications for Statistical Applications and Methods
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• v.18 no.4
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• pp.423-431
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• 2011

For procuring more sensitive information and estimating stratum target population proportion as well as an overall one form a sensitive population composed of several strata we suggest a two-stage stratified unrelated question model that uses stratified random sampling instead of simple random sampling in the two-stage unrelated question model by Kim et al. (1992) and extend it to the three-stage stratified unrelated question model. We also deal with the proportional and optimal allocation problems in each suggested model, compare the relative efficiency of the suggested two models, and show that the three-stage stratified unrelated question model is more efficient than the two-stage one in view of the variance.

• The Korean Journal of Applied Statistics
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• v.28 no.1
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• pp.75-82
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• 2015

We discuss confidence intervals for sensitive binomial attributes obtained by a direct question method and indirect question method. The Randomized Response Technique(RRT) by Warner (1965) is an indirect question method that uses a randomization device to reduce the response burden of respondents. We used the mean coverage probability (MCP), root mean squared error (RMSE), and mean expected width (MEW) to compare the confidence intervals by the two methods. The numerical comparisons indicated found that the MEW of RRT is too large and the RRT is so conservative that the MCP exceeds a nominal level(${\alpha}$); therefore, it is necessary to complement these problem in order to increase the utility of the indirect question method.

• Communications for Statistical Applications and Methods
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• v.7 no.2
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• pp.427-433
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• 2000

In this paper, we review several two-stage randomized response techniques for gathering self-report data when persons are asked sensitive question. Also efficiencies and privacy protections based on the two-stage randomized response procedures are compared. Finally, we find optimal parameter conditions.

• Journal of the Korean Statistical Society
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• v.16 no.2
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• pp.113-116
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• 1987

The role of randomization is examined with regard to the Simpson's paradox. When the sample size n is large, it is known that the randomization is powerful in preventing the Simpson's paradox. In the present study, the question is whether is performs well for small n.

• The Korean Journal of Applied Statistics
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• v.8 no.1
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• pp.27-38
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• 1995

In the surveys of sensitive issues of the population that is composed of several unknown-size stratum, we propose the unrelated question model with quantitative attribute by using stratified double sampling. And, we consider two types of sample allocations under the fixed cost, which are the proportional allocation, the optimum allocation. In efficiency, the proosed model is inferior to the unrelated question model with quantitative attribute by stratified sampling in case of the size of each stratum is known. But we find that efficiency of the proposed model is increased, when the selecting probability of sensitive question p is small and first stage sample size n' is large.