• Magazine of the Korean Society of Agricultural Engineers
• /
• v.45 no.3
• /
• pp.116-126
• /
• 2003

In this study, we research about the relationships of human longevity and environments, inducted the significant factors of longevity from the statistical analysis, and represented spatial distribution of longevity using geographic information system. The factors confining human longevity can be categorized by geography/geology, climate/weather, economy, and social welfare. After analyzing statistical data, dependent variable which means the longevity index is defined by the ratio of population more than 85 years old among population more than 65 years old. The results of analysis show that longevity are related with waterworks ratio, temperature, local tax ratio, and latitude. In this study we discussed about the spatial characteristics which are represented by variance of the longevity index and described a spatial relationship between the longevity index and significant factors which are chosen by statistical analysis. In the further study, in order to sustain the longevity of a region, it is necessary for the effective rural planning to propagate a longevity of rural areas.

• Journal of Korean Society for Quality Management
• /
• v.41 no.3
• /
• pp.487-494
• /
• 2013

Purpose: In this study, we propose the precision guided munitions verification methodology using the statistical analysis method has been proposed. and it can be applied to the precision guided munitions quality assurance work. Methods: This modeling is based on Failure Mode and Effects Analysis, Statistical Process Control, Defense Quality Managerment System, Production Readiness Review, Manufacturing Readiness Assesment and so on. Results: The Process Control Modeling that has the following procedures ; searching the critical to quality, statistical analysis by process, verify process. Moreover, the effectiveness of the methodology is verified by applying to the precision guided munitions. Conclusion: To achieve a analysis methods of statistical process control and verify process for precision guided munitions.

• Knowledge Management Research
• /
• v.20 no.2
• /
• pp.1-24
• /
• 2019

This tutorial introduces procedures and methods for performing structural equation modeling using R. To do this, we present advanced analysis methods based on structural equation model such as mediation effect analysis, moderation effect analysis, moderated mediation effect analysis, and multiple-group analysis with R program code using R lavaan package that supports structural equation modeling. R is flexible and scalable, unlike traditional commercial statistical packages. Therefore, new analytical techniques are likely to be implemented ahead of any other statistical package. From this point of view, R will be a very appropriate choice for applying new analytical techniques or advanced techniques that researchers need. Considering that various studies in the social sciences are applying structural equations modeling techniques and increasing interest in open source R, this tutorial is expected to be useful for researchers who are looking for alternatives to existing commercial statistical packages.

• Communications for Statistical Applications and Methods
• /
• v.7 no.2
• /
• pp.605-616
• /
• 2000

Three primary interests frequently raised by mortgage companies are introduced and the corresponding statistical approaches for the default probability in mortgage companies are examined. Statistical models considered in this paper are time series, logistic regression, decision tree, neural network, and discrete time models. Usage of the models is illustrated using an artificially modified data set and the corresponding models are evaluated in appropriate manners.

• Communications for Statistical Applications and Methods
• /
• v.6 no.1
• /
• pp.33-42
• /
• 1999

A method of detecting influential observations in principal factor analysis is suggested. it is based on a perturbation of the empirical distribution function and an adoption of the local influence method. An illustrative example is given.

• Proceedings of the Korea Society of Design Studies Conference
• /
• 2002.11b
• /
• pp.48-49
• /
• 2002

• Genomics & Informatics
• /
• v.15 no.1
• /
• pp.51-53
• /
• 2017

High-throughput transcriptome sequencing, also known as RNA sequencing (RNA-Seq), is a standard technology for measuring gene expression with unprecedented accuracy. Numerous bioconductor packages have been developed for the statistical analysis of RNA-Seq data. However, these tools focus on specific aspects of the data analysis pipeline, and are difficult to appropriately integrate with one another due to their disparate data structures and processing methods. They also lack visualization methods to confirm the integrity of the data and the process. In this paper, we propose an R-based RNA-Seq analysis pipeline called TRAPR, an integrated tool that facilitates the statistical analysis and visualization of RNA-Seq expression data. TRAPR provides various functions for data management, the filtering of low-quality data, normalization, transformation, statistical analysis, data visualization, and result visualization that allow researchers to build customized analysis pipelines.

• Journal of the Korea Society of Computer and Information
• /
• v.21 no.8
• /
• pp.77-84
• /
• 2016

In general statistical analysis, we need to make a normal assumption. If this assumption is not satisfied, we cannot expect a good result of statistical data analysis. Most of statistical methods processing the outlier and noise also need to the assumption. But the assumption is not satisfied in big data because of its large volume and heterogeneity. So we propose a methodology based on box-plot and data smoothing for controling outlier and noise in big data analysis. The proposed methodology is not dependent upon the normal assumption. In addition, we select patent documents as target domain of big data because patent big data analysis is a important issue in management of technology. We analyze patent documents using big data learning methods for technology analysis. The collected patent data from patent databases on the world are preprocessed and analyzed by text mining and statistics. But the most researches about patent big data analysis did not consider the outlier and noise problem. This problem decreases the accuracy of prediction and increases the variance of parameter estimation. In this paper, we check the existence of the outlier and noise in patent big data. To know whether the outlier is or not in the patent big data, we use box-plot and smoothing visualization. We use the patent documents related to three dimensional printing technology to illustrate how the proposed methodology can be used for finding the existence of noise in the searched patent big data.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.24 no.12
• /
• pp.999-1006
• /
• 2014

Mindlin plate theory includes the shear deformation and rotatory inertia effects which cannot be negligible as exciting frequency increases. The statistical methods such as energy flow analysis(EFA) and statistical energy analysis(SEA) are very useful for estimation of structure-borne sound of various built-up structures. For the reliable vibrational analysis of built-up structures at high frequencies, the energy transfer relationship between out-of-plane waves and in-plane waves exist in Mindlin plates coupled at arbitrary angles must be derived. In this paper, the new wave transmission analysis is successfully performed for various energy analyses of Mindlin plates coupled at arbitrary angles.

• Journal of Elementary Mathematics Education in Korea
• /
• v.24 no.1
• /
• pp.1-30
• /
• 2020

This study was carried out in order to identify the error types of statistical graphs for statistical literacy education. We analyze the meaning of using graphs in statistical problem solving, and identify categories, frequencies, and contexts as the components of statistical graphs. Error types of representing categories and frequencies make statistics consumers see incorrect distributions of data by subjective point of view of statistics producers and visual illusion. Error types of providing contexts hinder the interpretation of statistical information by concealing or twisting the contexts of data. Moreover, the findings show that tasks provide standardized frame already for drawing graphs in order to avoid errors and pay attention to the process of drawing the graph rather than statistical literacy for analyzing data. We suggest some implications about statistical literacy education, ethical problems, and knowledge for teaching to be considered when teaching the statistical graph in elementary mathematics classes.