• Proceedings of the Korean Society for Quality Management Conference
• /
• 2009.10a
• /
• pp.33-39
• /
• 2009

본 연구에서는 현장에서 6 시그마를 활용 시 통계분석의 기초가 되는 초기 데이터 분석에 대한 고찰이다. 통계의 가장 기본이 되는 데이터가 잘못되었으면 나머지 모두 문제가 된다. 이에 데이터 초기에 발생할 수 있는 여러 오류의 가능성을 살펴보고 각각에 대해 해결책을 제시하였다. 여기서 활용하는 방법들은 계측기 선정, Gage R&R, Histogram, Box-plot, PDF, Box-Cox 변화 등이다.

• 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.

• Journal of Integrative Natural Science
• /
• v.13 no.2
• /
• pp.76-82
• /
• 2020

If normality of an observed data is not a viable assumption, we can carry out normal-theory analyses by suitable transforming data. Power transformation by Box and Cox, one of the transformation methods, is derived the power which maximized the likelihood function. But it doesn't induces the closed form in mathematical analysis. In this paper, we compose some R the syntax of which is easier than other statistical packages for deriving the power with using numerical methods. Also, by using R, we show the transformed data approximately distributed the normal through Q-Q plot in univariate and bivariate cases with some examples. Finally, we present the value of a goodness-of-fit statistic(AD) and its p-value for normal distribution. In the similar procedure, this method can be extended to more than bivariate case.

• The Korean Journal of Applied Statistics
• /
• v.15 no.2
• /
• pp.433-448
• /
• 2002

Revelation is emphasized in exploratory data analysis. Hence, many graphical techniques are used in exploratory data analysis. Three applications of graphs in exploratory data analysis are presented.

• Journal of Applied Reliability
• /
• v.11 no.3
• /
• pp.213-224
• /
• 2011

In this paper, we analyze statistically the data set of first leak time of water pipeline. We classify first the leak time data by pipe type, location, diameter of pipe and, length of pipe. We perform the analysis of variance to indicate that there are significant difference of mean of the time between levels of the factor and also compare the distribution of levels using the multiple box-plot. When there are the difference of the mean, we perform the least significant test to find out what levels of the facor has a different mean.

• Journal of the Korean School Mathematics Society
• /
• v.1 no.1
• /
• pp.35-45
• /
• 1998

This paper will present some basic and simple graphical methods of exploratory data analysis for the instrument of data analysis at school mathematics. Human beings perceive visual patterns more readily than patterns in collections of numbers. This is especially important in exploratory data analysis because pictures dramatically reveal things that we did not expect to find in the data set. Here are graphical methods as the stem and leaf plot, the box plot, the star plot and the face plot. These methods impulse the motivation of students in real life. And the subject can be taught in secondary school with several applications. Also It is important for students to get a feel for working with and manipulating data before studying the more theoretical aspects of statistics.

• Journal of the Korean Data and Information Science Society
• /
• v.26 no.2
• /
• pp.399-408
• /
• 2015

This paper presented airquality data through data visualization in several ways and described its characteristics related to statistical methods for analysis. Software R was used for visualization tools. The airquality data was measured in New York city from May to September of year 1973. First, simple, exploratory data analysis was done in terms of both data visualization and analysis to find out univariate characteristics. Then through data transformation and multiple regression analysis, model for describing the airquality level was found. Also, after some data categorization, overall feature of the data was explored using box plot and three-dimensional perspective drawing and scatter plot.

• The Korean Journal of Applied Statistics
• /
• v.29 no.4
• /
• pp.657-678
• /
• 2016

This study deals with the effect of online word-of-mouth (OWOM) variables on the box office. From the result of statistical analysis on 276 films with audiences of more than five hundred thousand released in the Korea from 2012 to 2015, it can be seen that the variables showing the size of OWOM (such as the number of the portal movie rater, blog, and news after release) are associated more with the box office than the portal movie rating showing the direction of OWOM as well as variables showing the inherent properties of the film such as grade, nationality, release month, release season, directors, actors, and distributors.

• Proceedings of the Korean Institute of Building Construction Conference
• /
• 2023.05a
• /
• pp.137-138
• /
• 2023

This study proposed the optimal mixing time for pre-mixed cement and post mixed cement using the statistical analysis method of box plots. Pre-mixed cement can prevent material seegregation, strength loss, and quality variation if mixed for at least 60 seconds, and the data median is shown to be within the box range. Post-mixed cement should be mixed for at least 180 seconds to prevent material segregation, strength loss, and quality variation, and compressive strength tends to increase with longer vibrating times. Therefore, it is suggested that using pre-mixed cement can shorten the vibrating time and increase the productivity of the concrete.

• Asian Journal of Turfgrass Science
• /
• v.13 no.3
• /
• pp.171-176
• /
• 1999

Chrysanthemum showed worse grow of wilt to death during summer at the field which is Allium fistulosum (welsh onion) plants had been cultivated. This study was carried out to analysis of activative inhibitors of chrysanthemum from root exudate of Allium fistulosum. Bioassay experiments with welsh onion root exudate were conducted and the biologically active compounds were determined. The results were obtained as follows. The root exudate of welsh onion inhibited root and hypocotyl growth of chrysanthemum and lettuce at low concentration(10ppm). The inhibitory effects was higher in closed bottom box but with drain hole than in open bottom box plot. The inhibitory substance contained in root exudate was analysed as vanillic acid. This phenolic acid was also detected in stem-leaf and root of welsh onion.