• Communications for Statistical Applications and Methods
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• v.26 no.1
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• pp.35-46
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• 2019

Multivariate Confidence Region (MCR) cannot be used to obtain the confidence region of the mean vector of multivariate data when the normality assumption is not satisfied; however, the Quantile Confidence Region (QCR) could be used with a Multivariate Quantile Vector in these cases. The coverage rate of the QCR is better than MCR; however, it has a disadvantage because the QCR has a wide shape when the probability density function follows a bimodal form. In this study, we propose a Quantile Confidence Region using the Highest density (QCRHD) method with the Highest Density Region (HDR). The coverage rate of QCRHD was superior to MCR, but is found to be similar to QCR. The QCRHD is constructed as one region similar to QCR when the distance of the mean vector is close. When the distance of the mean vector is far, the QCR has one wide region, but the QCRHD has two smaller regions. Based on these features, it is found that the QCRHD can overcome the disadvantages of the QCR, which may have a wide shape.

• Journal of the Korea Society of Computer and Information
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• v.24 no.6
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• pp.159-164
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• 2019

The statistical inference of Cronbach's alpha measure of internal reliability is known to be inaccurate when sample size is small and the assumption of normality is violated. In this paper, we describe the permutation method in which we compute resampling p-values for testing the difference between two or more independent Cronbach's alpha coefficients. When the over-all permutation test is significant, we also make pairwise post-hoc comparisons using permutaion method. The permutation tests for the equality of two independent Cronbach's alpha coefficients and three independent Cronbach's alpha coefficients are illustrated with an example analysis of survey data.

• Asia pacific journal of information systems
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• v.33 no.2
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• pp.367-388
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• 2023

This study aimed to examine the factors of information-sharing intention on social networking sites (SNSs) by integrating the perspectives of the institution-based trust, social presence, and theory of reasoned action (TRA). An empirical survey was conducted and 364 valid respondents were collected from Facebook (FB) users in Taiwan. These data were analyzed against the research model using the partial least squares (PLS) structural equation modeling. The findings revealed that situational normality and structural assurance have a positive influenced user trust in SNSs which in turn increased their information-sharing attitudes. Furthermore, the subjective norms, user information-sharing attitudes and social presence of the SNSs were shown to have a positive influenced on user information sharing intention. Finally, this study provided several important theoretical and practical implications to understand factors affecting information-sharing intention on SNSs.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.3
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• pp.231-240
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• 2016

Recently, fake test data of power cables in nuclear power plants was a terrible shock to the citizens. Some cable companies manipulated the test data to make unfair profits. In addition, fake test data cases were found in military supplies. The fake test data cases focused on parts of army's tank, armored car. This paper propose a new method that can detect fake test data using known statistical methods. In addition, the method was implemented in Microsoft Excel to allow easy use. Lastly, a check sheet was proposed to check the validity of the test system of military suppliers. By detecting and checking the fake test data, it is expected that our new method will play an important role in quality assurance of military supplies.

• Journal of Preventive Medicine and Public Health
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• v.31 no.4 s.63
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• pp.875-884
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• 1998

Missing observations are common in medical research and health survey research. Several statistical methods to handle the missing data problem have been proposed. The EM algorithm (Expectation-Maximization algorithm) is one of the ways of efficiently handling the missing data problem based on sufficient statistics. In this paper, we developed statistical models and methods for survey data with multivariate missing observations. Especially, we adopted the EM algorithm to handle the multivariate missing observations. We assume that the multivariate observations follow a multivariate normal distribution, where the mean vector and the covariance matrix are primarily of interest. We applied the proposed statistical method to analyze data from a health survey. The data set we used came from a physician survey on Resource-Based Relative Value Scale(RBRVS). In addition to the EM algorithm, we applied the complete case analysis, which uses only completely observed cases, and the available case analysis, which utilizes all available information. The residual and normal probability plots were evaluated to access the assumption of normality. We found that the residual sum of squares from the EM algorithm was smaller than those of the complete-case and the available-case analyses.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.368-372
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• 2009

The method to get the feature have been proposed to recognize the user activity by setting specific action for making the user independent result in previous research. However, it was only applied in specific environment and it was difficult to implement because it regarded only some specific feature as the recognized object. To improve this problem we detected the normality/abnormality of the activity based on the repetition and the continuity of the past activity pattern. We applied the unsupervised learning method, not supervised, and clustered the data which was collected within a certain period of time and we regarded it as the basis of the evaluation of the repetition. We demonstrated to be able to detect the abnormal activity based on wether the data was generated repeatedly.

• Journal of the Korean Statistical Society
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• v.30 no.1
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• pp.41-61
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• 2001

The minimum negative exponential disparity estimator(MNEDE), introduced by Lindsay(1994), is an excellenet competitor to the minimum Hellinger distance estimator(Beran 1977) as a robust and yet efficient alternative to the maximum likelihood estimator in parametric models. In this paper we define the negative exponential deviance test(NEDT) as an analog of the likelihood ratio test(LRT), and show that the NEDT is asymptotically equivalent to he LRT at the model and under a sequence of contiguous alternatives. We establish that the asymptotic strong breakdown point for a class of minimum disparity estimators, containing the MNEDE, is at least 1/2 in continuous models. This result leads us to anticipate robustness of the NEDT under data contamination, and we demonstrate it empirically. In fact, in the simulation settings considered here the empirical level of the NEDT show more stability than the Hellinger deviance test(Simpson 1989). The NEDT is illustrated through an example data set. We also define a goodness-of-fit statistic to assess adequacy of a specified parametric model, and establish its asymptotic normality under the null hypothesis.

• The Journal of Industrial Distribution & Business
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• v.11 no.4
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• pp.7-18
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• 2020

Purpose: This research investigates the impact of technology adoption on organisation productivity. The framework has three independent variables viz. technological change, information technology (IT) infrastructure, and IT knowledge management and one dependent variable as organisational productivity. Research design, data and methodology: An explanatory research design with a quantitative research method was employed, and data was collected using a self-administered questionnaire using online as well as an offline survey. The sample consisted of 300 IT managers and senior-level executives (production as well as service team) in leading IT companies in Malaysia selected using snowball sampling. Normality and reliability assessment was performed in the first stage utilising SPSS 22, and Confirmatory Factory Analysis (CFA) was performed with maximum likelihood estimation to assess the internal consistency, convergent validity, and discriminant validity. Finally, Structural Equation Model (SEM) and path analysis are conducted using AMOS 22. Results: The research findings demonstrated that technological change and IT infrastructure positively and significantly impact the organisation's productivity while IT knowledge management has significant but negative impact on organizational productivity of IT companies in Malaysia. Conclusion: The research concludes that all three factors plays important role in deciding organizational producvity. Recommendations, implications, limitations and future research avenues are discussed.

• The Journal of Asian Finance, Economics and Business
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• v.5 no.4
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• pp.35-44
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• 2018

The study is aimed at investigating the main factors that affect the interest rate yields, in the long-term. In addition, the study surveys the theories and literature relating to the determinants of interest rate. The importance of which is essential not only for governments, but also for banks and corporate financial risk management decisions, including risk exposures in banks and capital markets. Interest rate influences corporate profit as well as growth. For this purpose, the study examines the impact of budget deficit, risk-free rate, capital inflows, money supply and business cycles on real interest rate in Jordan. These factors are based upon well-established theories and straightforward practical view as interest rate determinants. Using data for (1990-2015), the study employed Johansen's co-integrating test, which takes into consideration the long-term unsynchronized relationships. The data is tested for normality, symmetric correlations, covariance diagonal and unit root. The results show that the government budget deficit, short-term risk-free interest rate, capital inflows, money supply and business cycle are long-term determinants of the real interest rate in Jordan. The coefficients of government budget deficit, short-term risk-free rate, money supply and business cycle all are inversely affecting the real interest rate, while capital inflows has a positive impact on the real interest rate.

• The Korean Journal of Applied Statistics
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• v.22 no.3
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• pp.515-530
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• 2009

Evaporation from surface water bodies is influenced by a number of meteorological parameters. The rate of evaporation is primarily controlled by incoming solar radiation, air and water temperature and wind speed and relative humidity. In the present study, influence of weekly meteorological variables such as air temperature, relative humidity, bright sunshine hours, wind speed, wind velocity, rainfall on rate of evaporation has been examined using 35 years(1971-2005) of meteorological data. Statistical analysis was carried out employing linear regression models. The developed regression models were tested for goodness of fit, multicollinearity along with normality test and constant variance test. These regression models were subsequently validated using the observed and predicted parameter estimates with the meteorological data of the year 2005. Further these models were checked with time order sequence of residual plots to identify the trend of the scatter plot and then new standardized regression models were developed using standardized equations. The highest significant positive correlation was observed between pan evaporation and maximum air temperature. Mean air temperature and wind velocity have highly significant influence on pan evaporation whereas minimum air temperature, relative humidity and wind direction have no such significant influence.