• 간호행정학회지
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• 제19권1호
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• pp.146-154
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• 2013

Purpose: To do nursing research effectively requires an understanding of fundamental principles of statistical methods. In this article, some key statistical methods which are commonly used in nursing research are identified and summarized. Methods: Ninety-two original articles from the Journal of Korean Academy of Nursing Administration were reviewed. Statistical methods were classified and summarized for usage in research and occurrence of common errors. Results: Among the original articles reviewed, 58 statistical usages contained errors. Most errors were found in linear regression analysis, Pearson correlation analysis, and chi-square test. From the detection of statistical errors in usage, suggestions for appropriate statistical methods were made. Conclusion: In order to improve validity of original articles in the Journal of Korean Academy of Nursing Administration, clearly stated statistical usage and close editorial attention to statistical methods are needed. Understanding statistical methods is part of the process that researchers must use to determine both quality and usefulness of the research. Research findings will be used to guide nursing practice and reduce uncertainty in decision making. However, to understand how to interpret research results, it is important to be able to understand basic statistical concepts. Researchers should also choose statistical methods that match their purposes.

• Industrial Engineering and Management Systems
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• 제12권2호
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• pp.112-117
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• 2013

The $\overline{x}$ control chart for the process mean and either the R or s control chart for the process dispersion have been used together to monitor the manufacturing processes. However, it has been pointed out that this procedure is flawed by a fault that makes it difficult to capture the behavior of process condition visually by considering the relationship between the shift in the process mean and the change in the process dispersion because the respective characteristics are monitored by an individual control chart in parallel. Then, the ($\overline{x}$, s) control chart has been proposed to enable the process managers to monitor the changes in the process mean, process dispersion, or both. On the one hand, identifying which process parameters are responsible for out-of-control condition of process is one of the important issues in the process management. It is especially important in the ($\overline{x}$, s) control chart where some parameters are monitored at a single plane. The previous literature has proposed the multiple decision method based on the statistical hypothesis tests to identify the parameters responsible for out-of-control condition. In this paper, we propose how to identify parameters responsible for out-of-control condition using the information criterion. Then, the effectiveness of proposed method is shown through some numerical experiments.

• Transactions on Electrical and Electronic Materials
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• 제12권3호
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• pp.115-118
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• 2011

Process characterization of the chemical mechanical polishing (CMP) process for undensified phosphosilicate glass (PSG) film is reported using design of experiments (DOE). DOE has been addressed to experimenters to understand the relationship between input variables and responses of interest in a simple and efficient way. It is typically beneficial for determining the adequate size of experiments with multiple process variables and making statistical inferences for the responses of interests. Equipment controllable parameters to operate the machine include the down force (DF) of the wafer carrier, pressure on the backside of the wafer, table and spindle speed (SS), slurry flow rate, and pad condition. None of them is independent; thus, the interaction between parameters also needs to be indicated to improve process characterization in CMP. In this paper, we have selected the five controllable equipment parameters, such as DF, back pressure (BP), table speed (TS), SS, and slurry flow (SF), most process engineers recommend to characterize the CMP process with respect to material removal rate (RR) and film uniformity as a percentage. The polished material is undensified PSG. PSG is widely used for the plananization in multi-layered metal interconnects. We identify the main effect of DF, BP, and TS on both RR and film uniformity, as expected, by the statistical modeling and analysis on the metrology data acquired from a series of $2^{5-1}$ fractional factorial design with two center points. This revealed the film uniformity of the polished PSG film contains two and three-way interactions. Therefore, one can easily infer that the process control based on better understanding of the process is the key to success in semiconductor manufacturing, typically when the wafer size reaches 300 mm and is continuously scheduled to expand up to 450 mm in or little after 2012.

• Korean Chemical Engineering Research
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• 제45권1호
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• pp.32-38
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• 2007

통계적인 공정 제어 기법을 회분식 공정에 적용하여, 일반적인 회분식 공정의 데이터를 통해 보다 빠르고, 손쉽게 공정의 상태를 진단할 수 있는 시스템을 구현해 보았다. 대표적인 회분식 공정의 하나인 반도체 식각공정과 반회분식 스타이렌-부타디엔 고무 생산 공정의 데이터를 이용하여 공정 변수와 공정의 상태간의 연관 관계를 규명할 수 있는 모델을 수립하였으며, 이 모델의 출력(output) 결과를 이용해 통계적 공정 제어 차트를 구성하고, 시간에 따른 공정의 추이를 분석해 이상을 판별해 보았다. 회분식 공정의 다축(multi-way) 데이터를 두개의 축으로 만드는 펼치기(unfolding) 과정을 거쳤으며, 모델링 방법으로는 Support Vector Regression 및 Partial Least Square 등의 다변량 회귀분석 방법을 이용하였다. 또한 에러차트 및 변수 기여도 차트(variable contribution chart)를 이용해 이상의 세기, 형태 및 이상 데이터에 대한 각 변수들의 기여도를 계산해 보았으며, 그 결과 이상의 발생 유무 및 발생시점 뿐만아니라 이상의 세기 및 원인 까지 진단해 볼 수 있는 우수한 성능을 보이는 것을 확인할 수 있었다.

• Communications for Statistical Applications and Methods
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• 제19권3호
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• pp.395-403
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• 2012

Process adjustment, also called engineering process control(EPC), is applied to maintain process output close to a target value by manipulating controllable variables, but special causes may still make the process deviate from the target and result in significant costs. Thus, it is important to detect and mediate deviations as early as possible. We propose a one-step detection method, the moving search block(MSB), with which the time and type of a special cause can be identified in short periods. A modified control rule that can entertain the effects of the special cause is proposed. A numerical example is presented to evaluate the performance of the proposed scheme.

• Communications for Statistical Applications and Methods
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• 제22권6호
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• pp.625-637
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• 2015

We develop a Bayesian clustering procedure based on a Dirichlet process prior with cluster specific random effects. Gibbs sampling of a normal mixture of linear mixed regressions with a Dirichlet process was implemented to calculate posterior probabilities when the number of clusters was unknown. Our approach (unlike its counterparts) provides simultaneous partitioning and parameter estimation with the computation of the classification probabilities. A Monte Carlo study of curve estimation results showed that the model was useful for function estimation. We find that the proposed Dirichlet process mixture model with cluster specific random effects detects clusters sensitively by combining vague edges into different clusters. Examples are given to show how these models perform on real data.

• Journal of the Korean Statistical Society
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• 제35권4호
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• pp.397-407
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• 2006

A new stochastic process is introduced for describing a mechanism of viruses. The process generalizes the $Bartoszy\'{n}ski's$ process ($Bartoszy\'{n}ski$, 1975a, 1975b, 1976) by allowing the stochastic perturbation between consecutive jumps to take into account the persistent infection (the infection without breaking infected cells). It is shown that the new process can be obtained by a weak limit of a sequence of Markov branching processes. Along with the construction of the new process, we study how the stochastic perturbation influences the risk of a symptom in an infected host. For this purpose, the quantal response model and the threshold model are investigated and compared through their induced survival functions.

• Journal of the Korean Statistical Society
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• 제35권4호
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• pp.355-376
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• 2006

To identify whether the sequence of observations follows a chain dependent process and whether the chain dependent or repeated observations follow stationary process or not, alternative procedures are suggested in this paper. These test procedures are formulated on the basis of logistic regression model under the likelihood ratio test criterion and applied to the daily rainfall occurrence data of Bangladesh for selected stations. These test procedures indicate that the daily rainfall occurrences follow a chain dependent process, and the different types of transition probabilities and overall transition probabilities of Markov chain for the occurrences of rainfall follow a stationary process in the Mymensingh and Rajshahi areas, and non-stationary process in the Chittagong, Faridpur and Satkhira areas.

• Journal of the Korean Statistical Society
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• 제23권2호
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• pp.483-498
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• 1994

Suppose that a stationary process ${X_t}$ has a marginal distribution whose support consists of sufficiently large integers. We are concerned with some analogous law of large numbers for such distribution function F. In particular, we determine a weak law of large numbers for maximum queueing length in $M/M\infty$ system. We also present a limiting behavior for the maxima based on AR(1) process with binomial thining and poisson marginals (INAR(1)) introduced by E. Mckenzie. It turns out that the result of AR(1) process is the same as that of $M/M/\infty$ queueing process in limit when we observe the queues at regularly spaced intervals of time.

• Communications for Statistical Applications and Methods
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• 제23권5호
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• pp.423-432
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• 2016

In this paper, we stochastically analyze the continuous time surplus process in a risk model which involves a continuous type investment. It is assumed that the investment of the surplus to other business is continuously made at a constant rate, while the surplus process stays over a given sufficient level. We obtain the stationary distribution of the surplus level and/or its moment generating function by forming martingales from the surplus process and applying the optional sampling theorem to the martingales and/or by establishing and solving an integro-differential equation for the distribution function of the surplus level.