• Journal of Korean Medicine Rehabilitation
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• v.20 no.4
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• pp.105-130
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• 2010

Objectives : The purpose of this study was to assess the statistical methods errors used in the journal of Oriental Rehabilitation Medicine(JORM) and to identify the types of errors in statistical analysis. Methods : We reviewed quantitative articles that were published in the JORM from January 2005 through October 2009. Those were not used by statistical analysis such as literature studies, case study, review articles were not included in this analysis. A total of 296 articles was reviewed. We evaluated the adequacy and the validity of the statistical techniques with our checklist established be modified Lee's checklist, and three statistical evaluators assessed together to minimize bias. Results : Of the 222 articles, 213 were used in inferential and descriptive statistics. Of those 80% of articles adopting descriptive and inferential statistics were detected having statistical errors. One articles used 1.7 statistical method unit generally. Most frequently employed statistics were student t-test, one way ANOVA. pearson correlation analysis, Mann-whitney U test, paired t-test, and chi-square test in their order. However, most frequent statistics having errors were similar in order. The most common statistic errors were as follow: 1. absence of normality test, 2. misuse between paired test and unpaired test, 3. wrong choice of repeated measures analysis without consideration of time variables, 4, increase of Type I error by using inappropriate multiple test, 5. inappropriate application of discrete or categorical data instead of continuous data in correlation analysis, 6. poor consideration of basic consumption in chi-square test, 7. confusion between frequency comparison and average comparison, 8. mentioning the statistical technique without using it. Conclusions : We found various mistake or misuses in the applications of statistical methodologies in the articles published in the JORM. Careful consideration of statistical use and review from the specialist of statistics are warranted for improving the quality of JORM.

• Communications for Statistical Applications and Methods
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• v.29 no.2
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• pp.225-238
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• 2022

In this paper, we propose a clustering method for advanced metering infrastructure (AMI) data in Korea. As AMI data presents non-stationarity, we consider time-dependent frequency domain principal components analysis, which is a proper method for locally stationary time series data. We develop a new clustering method based on time-varying eigenvectors, and our method provides a meaningful result that is different from the clustering results obtained by employing conventional methods, such as K-means and K-centres functional clustering. Simulation study demonstrates the superiority of the proposed approach. We further apply the clustering results to the evaluation of the electricity price system in South Korea, and validate the reform of the progressive electricity tariff system.

• The Transactions of the Korea Information Processing Society
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• v.7 no.4
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• pp.1150-1159
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• 2000

This paper presents an automatic text categorization model that improves the accuracy by combining statistical and knowledge-based categorization methods. In our model we apply knowledge-based method first, and then apply statistical method on the text which are not categorized by knowledge-based method. By using this combined method, we can improve the accuracy of categorization while categorize all the texts without failure. For statistical categorization, the vector model with Inverted Category Frequency (ICF) weighting is used. For knowledge-based categorization, Phrasal Patterns and Keyword Sets are introduced to represent sentence patterns, and then pattern matching is performed. Experimental results on new articles show that the accuracy of categorization can be improved by combining the tow different categorization methods.

• Journal of Ocean Engineering and Technology
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• v.34 no.6
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• pp.428-435
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• 2020

Energy flow analysis (EFA) has been used to predict the frequency-averaged vibrational responses of built-up structures at high frequencies. In this study, the frequency-averaged exact energetics of the in-plane motions of the plate were derived for the first time by solving coupled partial differential equations. To verify the EFA for the in-plane waves of the plate, numerical analyses were performed on various coupled plate structures. The prediction results of the EFA for coupled plate structures were shown to be accurate approximations of the frequency-averaged exact energetics, which were obtained from classical displacement solutions. The accuracy of the results predicted via the EFA increased with an increase in the modal density, regardless of various structural parameters. Therefore, EFA is an effective technique for predicting the frequency-averaged vibrational responses of built-up structures in the high frequency range.

• The Korean Journal of Applied Statistics
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• v.25 no.6
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• pp.925-932
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• 2012

The article introduces a method to estimate a cointegrated vector autoregressive model, using mixed-frequency data, in terms of a state-space representation of the vector error correction(VECM) of the model. The method directly estimates the parameters of the model, in a state-space form of its VECM representation, using the available data in its mixed-frequency form. Then it allows one to compute in-sample smoothed estimates and out-of-sample forecasts at their high-frequency intervals using the estimated model. The method is applied to a mixed-frequency data set that consists of the quarterly real gross domestic product and three monthly coincident indicators. The result shows that the method produces accurate smoothed and forecasted estimates in comparison to a method based on single-frequency data.

• Journal of The Korean Astronomical Society
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• v.46 no.2
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• pp.65-74
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• 2013

We probe the feasibility of high-frequency radio observations of very rapid flux variations in compact active galactic nuclei (AGN). Our study assumes observations at 230GHz with a small 6-meter class observatory, using the SNU Radio Astronomical Observatory (SRAO) as an example. We find that 33 radio-bright sources are observable with signal-to-noise ratios larger than ten. We derive statistical detection limits via exhaustive Monte Carlo simulations assuming (a) periodic, and (b) episodic flaring flux variations on time-scales as small as tens of minutes. We conclude that a wide range of flux variations is observable. This makes high-frequency radio observations-even with small observatories-a powerful probe of AGN intra-day variability; especially, those which complement observations at lower radio frequencies with larger observatories like the Korean VLBI Network (KVN).

• Journal of the Korea Institute of Military Science and Technology
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• v.5 no.3
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• pp.11-22
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• 2002

In this paper, a statistical meaning that the 1% frequency value which is used as a basis for the temperature specification generation for weapon systems is similar to $3{\sigma}$ frequency value of a year is presented, and the theoretical reference for temperature specification generation is made. The new method which extracts the 1% frequency value from general weather data, not depending on long term temperature hour data, is established, and the temperature analysis result of East Asia is also presented by using this method. On the basis of these result, operational temperature for the weapon systems to be used in the area of East Asia is recommended.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.07b
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• pp.927-930
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• 2002

The HFPD measurement method is a technique to analyze aging state of high voltage insulation materials and detect higher frequency signals than conventional PD measurement method therefore it takes less noise effect and could execute active line measurement. It is possible to analyze main discharge phenomena and obtain access to aging progress occurred in insulation materials through accumulation of HFPD signals during determined interval and expression of fractal dimension using statistical process of accumulated signals. In this study, the statistical parameters (skewness & kurtosis) and fractal dimensions are changed by discharge patterns that is shown up different characteristics with applied voltages and times.

• The Korean Journal of Applied Statistics
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• v.29 no.3
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• pp.505-512
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• 2016

The paper is concerned with high frequency financial time series. A weighted hybrid volatility is suggested to compute daily volatilities based on high frequency data. Various realized volatility (RV) computations are reviewed and the weights are chosen by minimizing the differences between the hybrid volatility and the realized volatility. A high frequency time series of KOSPI200 index is illustrated via QLIKE and Theil-U statistics.

• Culinary science and hospitality research
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• v.21 no.6
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• pp.49-62
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• 2015

Give that statistical analysis is an essential component of foodservice-related research, the purpose of this review is to analyse research trends of statistical methods applied to foodservice-related research. To achieve these objective, this study carried out a content analysis on a total of 251 out of 415 research articles published in The Korean Journal of Culinary Research(TKJCR) from January 2010 to December 2013. Of the total 164 research articles focussing on natural science research, qualitative research, articles written in English were excluded from the scope of this study. The results of this study are as follows. First, it turned out that 269 research articles applied quantitative research methods, and only 10 articles applied qualitative research methods among the 279 research articles based on social science research methods. Second, 20 article (8.0%) among the 251 did not specify the statistical methods or computer programs that were used for statistical analysis. Third, it was found that 228 articles (90.8%) used the SPSS program for data analysis. Fourth, in terms of frequency of use, it was revealed frequency analysis was most used, followed in order by reliability analysis, exploratory factor analysis, correlation analysis, regression analysis, structural equation modeling, confirmatory factor analysis, t-test, variance analysis, and cross tabs analysis, However, 3 out of 56 research articles that used a t-test did not suggest a t-value. 10 out of 64 articles that used ANOVA and demonstrated a significant difference in between-group mean did not conducted post-hoc test. Therefore, the researchers with interest in foodservice fields need to keep in mind that choosing and applying the correct statistical technique both determine the value and the success or failure of a study. To enhance the value and success of a study, it is necessary to use the proper statistical technique in an efficient way in order to prevent statistical errors.