• Restorative Dentistry and Endodontics
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• v.49 no.2
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• pp.21.1-21.8
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• 2024

Objectives: This paper aims to serve as a useful guide for sample size determination for various correlation analyses that are based on effect sizes and confidence interval width. Materials and Methods: Sample size determinations are calculated for Pearson's correlation, Spearman's rank correlation, and Kendall's Tau-b correlation. Examples of sample size statements and their justification are also included. Results: Using the same effect sizes, there are differences between the sample size determination of the 3 statistical tests. Based on an empirical calculation, a minimum sample size of 149 is usually adequate for performing both parametric and non-parametric correlation analysis to determine at least a moderate to an excellent degree of correlation with acceptable confidence interval width. Conclusions: Determining data assumption(s) is one of the challenges to offering a valid technique to estimate the required sample size for correlation analyses. Sample size tables are provided and these will help researchers to estimate a minimum sample size requirement based on correlation analyses.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.6
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• pp.43-49
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• 2001

A reduced machining time and increased accuracy for the sculptured surface are very important when producing complicated parts. The step-size and tool-path interval are essential components in high speed and high resolution machining. If they are small, the machining time will increase, whereas if they are large, rough surfaces will be caused. In particular, the machining time, which is key in high speed machining, is affected by the tool-path interval more than the step-size. The conventional method for calculating the tool=path interval is to select a small parametric increment of a small increment based on the curvature of the surface. However, this approach also has limitations. The first is that the tool-path interval can not be calculated precisely. The second is that a separate tool-path interval needs to be calculated in each of the three cases. The third is that the conversion from Cartesian domain to parametric domain or vice versa must be necessary. Accordingly, the current study proposes a new tool-path interval algorithm that do not involve a curvature and that is not necessary for any conversion and a variable step-size algorithm for NURBS.

• Proceedings of the Safety Management and Science Conference
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• 2012.11a
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• pp.461-471
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• 2012

Most useful statistical techniques in six sigma DMAIC are hypothesis testing and interval estimation. So this paper reviews and derives sample size formula by considering significance level, power of detectability and effect difference. The quality practioners can effectively interpret the practical and statistical significance with the rational sample sizing.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.163-164
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• 2011

본고에서는 Multi-class Jobs을 Dispatching system 에서 처리하는 경우, Cost performance 을 점근적으로 해석하는 과정에 대해 논의한다. 구체적으로, Job 할당 시스템은 Size-Interval 기반의 스케줄링 기법을 이용하고, Resource failure 에 대비하여 Job duplication 전략을 활용하는 것으로 가정 한다.

• Journal of the Korean Society of Clothing and Textiles
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• v.27 no.8
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• pp.1004-1013
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• 2003

This study addressed an ill-understood issue of a price response model and a monopolistic price interval of fashion goods. The concept of monopolistic price interval introduced by Gutenberg has been rarely applied to the fashion goods, which is known as price sensitive goods. Thus, this study examined the price insensitive zone of the blue jean. The data of 268 respondents were analyzed using Choice-based Conjoint (CBC) analysis and t-test. Considering brand consideration set as a price determinant, we found the presence of monopolistic price interval of the jean. The results obtained from the CBC analysis showed that the bigger the size of brand consideration set, the shorter the monopolistic interval. This implied that the consumer who had a small brand consideration set was more likely to have a longer monopolistic price interval than the one who had a large brand consideration set, since the consumer with a small consideration set tended to value brand itself more than price. Although significant monopolistic price intervals were shown only for the three jean brands out of the seven, to reduce the size of brand consideration set and to increase brand loyalty were found important in maximizing firms'financial profits.

• Communications for Statistical Applications and Methods
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• v.16 no.2
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• pp.363-372
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• 2009

The difference of two independent binomial proportions is frequently of interest in biomedical research. The interval estimation may be an important tool for the inferential problem. Many confidence intervals have been proposed. They can be classified into the class of exact confidence intervals or the class of approximate confidence intervals. Ore may prefer exact confidence interval s in that they guarantee the minimum coverage probability greater than the nominal confidence level. However, someone, for example Agresti and Coull (1998) claims that "approximation is better than exact." It seems that when sample size is large, the approximate interval is more preferable to the exact interval. However, the choice is not clear when sample, size is small. In this note, an exact confidence and an approximate confidence interval, which were recommended by Santner et al. (2007) and Lee (2006b), respectively, are compared in terms of the coverage probability and the expected length.

• Journal of Korean Society of Transportation
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• v.35 no.1
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• pp.63-78
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• 2017

The purpose of this study is to determine the optimal aggregation interval to increase the reliability when estimating representative value of individual vehicle travel time collected by DSRC equipment in interrupted traffic flow section in National Highway. For this, we use the bimodal asymmetric distribution data, which is the distribution of the most representative individual vehicle travel time collected in the interrupted traffic flow section, and estimate the MSE(Mean Square Error) according to the variation of the aggregation interval of individual vehicle travel time, and determine the optimal aggregation interval. The estimation equation for the MSE estimation utilizes the maximum estimation error equation of t-distribution that can be used in asymmetric distribution. For the analysis of optimal aggregation interval size, the aggregation interval size of individual vehicle travel time was only 3 minutes or more apart from the aggregation interval size of 1-2 minutes in which the collection of data was normally lost due to the signal stop in the interrupted traffic flow section. The aggregation interval that causes the missing part in the data collection causes another error in the missing data correction process and is excluded. As a result, the optimal aggregation interval for the minimum MSE was 3~5 minutes. Considering both the efficiency of the system operation and the improvement of the reliability of calculation of the travel time, it is effective to operate the basic aggregation interval as 5 minutes as usual and to reduce the aggregation interval to 3 minutes in case of congestion.

• Korean Journal of Plant Resources
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• v.19 no.4
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• pp.521-523
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• 2006

This experiment was carried out to find out proper pot size and bottom irrigation interval for the flowerpot cultivation of Cyrtomium falcatum, 3 different pot sizes (5, 7, 10cm in diameter) and 3 irrigation interval (1 day, 3 days, 5 days) were treated by completely randomized design with 3 replications. Growth characteristics of Cyrtomium falcatum were investigated every 30 days after planting. The pot size of 7 to 10cm in diameter and the irrigation interval of 5 days appeared to be appropriate for Cyrtomium falcatum cultivation.

• Journal of Korean Society for Quality Management
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• v.32 no.4
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• pp.252-264
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• 2004

Variable sampling Interval (VSI) control charts vary the sampling interval according to value of the control statistic while the sample size is fixed. It is known that control charts with 2-state VSI scheme, which uses only two sampling intervals, give good statistical properties. Variable sample size (VSS) control charts vary the sample size according to value of the control statistic while the sampling interval is fixed. In the VSS scheme no optimal results are known for the number of sample sizes. It is also known that the variable sampling rate (VSR) $\bar{X}$ control chart with 2-state VSS and 2-state VSI scheme leads to large improvements In performance over the fixed sampling rate (FSR) $\bar{X}$ chart, but the optimal number of states for sample size Is not known. In this paper, the VSR Χ charts with multi-state VSS and 2-state VSI scheme are designed and compared to 2-state VSS and 2-state VSI scheme. The multi-state VSS scheme is considered to, achieve an additional improvement by switching from the 2-state VSS scheme. On the other hand, the multi-state VSI scheme is not considered because the 2-state scheme is known to be optimal. The 3-state VSS scheme improves substantially the sensitivity of the $\bar{X}$ chart especially for small and moderate mean shifts.

• The Korean Journal of Applied Statistics
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• v.27 no.2
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• pp.331-343
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• 2014

We propose two estimating procedures to analyze clustered interval-censored data with an informative cluster size based on a marginal model and investigate their asymptotic properties. One is an extension of Cong et al. (2007) to interval-censored data and the other uses the within-cluster resampling method proposed by Hoffman et al. (2001). Simulation results imply that the proposed estimators have a better performance in terms of bias and coverage rate of true value than an estimator with no adjustment of informative cluster size when the cluster size is related with survival time. Finally, they are applied to lymphatic filariasis data adopted from Williamson et al. (2008).