• Advances in nano research
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• v.14 no.3
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• pp.225-234
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• 2023

In this study, we aim to use big data resources and statistical analysis to obtain a reliable instruction to reach high-quality and high yield agricultural yields. In this regard, soil type data, raining and temperature data as well as wheat production in each year are collected for a specific region. Using statistical methodology, the acquired data was cleaned to remove incomplete and defective data. Afterwards, using several classification methods in machine learning we tried to distinguish between different factors and their influence on the final crop yields. Comparing the proposed models' prediction using statistical quantities correlation factor and mean squared error between predicted values of the crop yield and actual values the efficacy of machine learning methods is discussed. The results of the analysis show high accuracy of machine learning methods in the prediction of the crop yields. Moreover, it is indicated that the random forest (RF) classification approach provides best results among other classification methods utilized in this study.

• Journal of the Korea Safety Management & Science
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• v.11 no.2
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• pp.159-165
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• 2009

Through the understanding of the change of productivity and the ability of error recovery according to aging and the assessment and analysis of them, we may take this research to contribute to make a design for the road-map to help set up the policy of employment for old generation. For this we have taken an experiment of the coordination tester for 100 person who are chosen randomly and analysed the collected data using SAS, which is one of widely used statistical analysis packages. The main results are as follow: $\circledcirc$ The result of regression between the working speed and the length of the correction of error shows independence. (pr>0.2029). $\circledcirc$ The regression between age and working speed is statistically significant. (pr<0.0001) $\circledcirc$ The relation between age and the length of the correction of error is not significant. (pr>0.9123).

• Journal of Digital Convergence
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• v.12 no.9
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• pp.275-282
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• 2014

The aim of this study was to investigate the statistical trend and errors of articles in the journal of Korean society of computed tomographic technology for contribution to the academic development of the professional society. Preliminary findings indicate that there are various statistical errors in the papers in the journal of Korean society of computed tomographic technology. Results suggest that the statistical education needs to be strengthened from university education to instructional course lecture of academic society. The improvement of the quality of the paper by improving awareness of the statistical error.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.12
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• pp.31-36
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• 2007

This paper presents a novel statistical characterization for accurate timing analysis in Partially-Depleted Silicon-On-Insulator (PD-SOI) circuits in BSIMSOI3.2 100nm technology. The proposed timing estimate algorithm is implemented in Matlab, Hspice, and C, and it is applied to ISCAS85 benchmarks. The results show that the error is within 5% compared with Monte Carlo simulation results.

• Communications for Statistical Applications and Methods
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• v.15 no.5
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• pp.737-752
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• 2008

About 1800, mathematicians combined analysis of error and probability theory into error theory. After developed by Gauss and Laplace, error theory was widely used in branches of natural science. Motivated by the successful applications of error theory in natural sciences, scientists like Adolph Quetelet tried to incorporate social statistics with error theory. But there were not a few differences between social science and natural science. In this paper we discussed topics raised then. The problems considered are as follows: the interpretation of individual man in society; the arguments against statistical methods; history of the measures for diversity. From the successes and failures of the $19^{th}$ century social statisticians, we can see how statistics became a science that is essential to both natural and social sciences. And we can see that those problems, which were not easy to solve for the $19^{th}$ century social statisticians, matter today too.

• Journal of Sasang Constitutional Medicine
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• v.28 no.1
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• pp.51-56
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• 2016

Objectives This study was to identify the types of errors in the statistical analysis and trends of previous reported papers that used various statistical techniques.Methods We have selected 118 original articles for statistical review from the OASIS(http://oasis.kiom.re.kr) and the Pubmed(http://www.pubmed.gov) in the field of Sasang constitutional medicine. Published year was restricted from 2011 to 2015.Results 1. The ANOVA(25.72%) was the statistic of choice overall, followed by the chi-square test(21.74%), regression analysis(14.13%), t-test(11.59%), and etc. 2. By examining the errors of the statistical methods, there were 42(59.2%) thesis with errors among 71 thesis using ANOVA, 19(31.7%) thesis among 60 thesis using chi-square test, and 35(89.7%) over 39 thesis using regression analysis.Conclusions To improve the quality of Sasang Constitution, the participation of statisticians in research design will reduce the significant errors in statistical interpretation of the results.

• Magazine of the Korean Society of Agricultural Engineers
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• v.40 no.1
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• pp.68-77
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• 1998

The purpose of this paper is to establish a method estimating the daily urban water demand using statistical analysis that is used for developing the efficient management and operation of the water supply facilities, and accurary of the model is verified by error rate and F-value. The data used in this study were the daily urban water use, the weather conditions such as temperature, precipitation, relative humidity, etc, and the day of The week. The case study was taken placed for the city of Namwon in Korea. The raw data used in this study were rearranged either by month or by season for analysis purpose, and the statistical analysis was applied to the data to obtain the regression model As a result of this study, the linear regression model was developed to estimate the daily urban water use with weather condition. The regression constant and coefficients of the model were determined for each month of a year. The accuracy of the model was within 3% of average error and within 11% of maximum error. The resulting model was found to he useful to the practical operation and management of the water supply facilities.

• Journal of the Society of Naval Architects of Korea
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• v.48 no.5
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• pp.426-434
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• 2011

Accurate weight prediction methods are an essential of the ship design in both ship cost managements and performance satisfactions. When no parent or similar ships are available, an adequate method of the ship weight estimating is required. In this study, there was carried out to develop the ship weight estimating method for the preliminary design phase. The weight estimating methods were first surveyed by the references and summarized their characteristics. The weight estimation method by statistical approach was developed for the container ship because the containerized transportation markets is gradually growing and ship's size and loading capacity are rapidly enlarged. The correlation analysis and the multiple regression analysis were used for developing the weight estimating method. As a results of evaluating the developed method, the error ratio of the variation between estimated weight and ship's data was about 5%. And it was only 1% difference with the calculating weight of conceptual design results by shipyard design team that the estimating weight of ultra-large container ship was predicted by the developed method.

• Communications for Statistical Applications and Methods
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• v.24 no.5
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• pp.507-518
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• 2017

Volatility plays a crucial role in theory and applications of asset pricing, optimal portfolio allocation, and risk management. This paper proposes a combined model of autoregressive moving average (ARFIMA), generalized autoregressive conditional heteroscedasticity (GRACH), and skewed-t error distribution to accommodate important features of volatility data; long memory, heteroscedasticity, and asymmetric error distribution. A fully Bayesian approach is proposed to estimate the parameters of the model simultaneously, which yields parameter estimates satisfying necessary constraints in the model. The approach can be easily implemented using a free and user-friendly software JAGS to generate Markov chain Monte Carlo samples from the joint posterior distribution of the parameters. The method is illustrated by using a daily volatility index from Chicago Board Options Exchange (CBOE). JAGS codes for model specification is provided in the Appendix.

• Communications for Statistical Applications and Methods
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• v.12 no.2
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• pp.305-312
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• 2005

In the cluster analysis, Hotelling's $T^2$ can be used to estimate the unknown number of clusters based on the idea of multiple comparison procedure. Especially, its threshold is obtained according to the probability of committing the type one error. Examples are used to compare Hotelling's $T^2$ with other classical location test statistics such as Sum-of-Squared Error and Wilks' $\Lambda$ The hierarchical clustering is used to reveal the underlying structure of the data. Also related criteria are reviewed in view of both the between variance and the within variance.