• 제목/요약/키워드: methods of data analysis

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재무비율을 이용한 농촌 중.노년기 가계의 재정상태 평가 (An Evaluation of Farm Households' Financial Status Using Financial Ratios)

  • 최현자
    • 가정과삶의질연구
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    • 제16권2호
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    • pp.83-96
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    • 1998
  • The purpose of this study was to investigate the level of assets and liabilities of farm households and to evaluate the financial status of rural middle-aged and old-aged household using financial ratios. For these purposes an empirical survey data was gathered from rural middle-aged and old-aged households in 8 provinces using structured questionnaires. 877 households data were used in final analysis. The statistical methods used for data analysis are frequency percentile mean The statistical methods used for data analysis are frequency percentile mean median standard deviation $\chi$2 and t-test using SPSS/PC WIN program. Among financial ratios 64.7% of total households could meet the guideline of consumption to income ratio 5.9% of total households could meet the appropriate level of short-term and long-term liquidity. In the case of debt burden ration 82% of total households could meet the guideline. And 28.5% of total households could meet the guideline of capital stock ratio .

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프랙탈 보간에 의한 엔드밀링 절삭력 예측 (End-milling Force Estimation by Fractal Interpolation)

  • 정진석;진도훈;윤문철
    • 한국기계가공학회지
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    • 제5권1호
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    • pp.7-12
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    • 2006
  • Recently, the fractal interpolation methods have been widely introduced and used to estimate and analyze various theoretical and experimental data. Because of the chaotic behaviors of dynamic cutting force data, some method for end-milling force analysis must be used. The fractal analysis used in this paper is fractal linear interpolation and fractal dimension. Also, several methods for computing fractal dimensions have been used in which the fractal dimension of the typical dynamic end-milling force was calculated according to number of data points that are generally lower than 200 data points sampled. This fractal analysis shows a possible prediction of end-milling force that has some dynamic chatter property or stationary property in endmilling operation.

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Compositional data analysis by the square-root transformation: Application to NBA USG% data

  • Jeseok Lee;Byungwon Kim
    • Communications for Statistical Applications and Methods
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    • 제31권3호
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    • pp.349-363
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    • 2024
  • Compositional data refers to data where the sum of the values of the components is a constant, hence the sample space is defined as a simplex making it impossible to apply statistical methods developed in the usual Euclidean vector space. A natural approach to overcome this restriction is to consider an appropriate transformation which moves the sample space onto the Euclidean space, and log-ratio typed transformations, such as the additive log-ratio (ALR), the centered log-ratio (CLR) and the isometric log-ratio (ILR) transformations, have been mostly conducted. However, in scenarios with sparsity, where certain components take on exact zero values, these log-ratio type transformations may not be effective. In this work, we mainly suggest an alternative transformation, that is the square-root transformation which moves the original sample space onto the directional space. We compare the square-root transformation with the log-ratio typed transformation by the simulation study and the real data example. In the real data example, we applied both types of transformations to the USG% data obtained from NBA, and used a density based clustering method, DBSCAN (density-based spatial clustering of applications with noise), to show the result.

오믹스 자료를 이용한 정준방법 비교 (A comparison study of canonical methods: Application to -Omics data)

  • 이승수;민은정
    • 응용통계연구
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    • 제37권2호
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    • pp.157-176
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    • 2024
  • 생명현상의 복잡한 시스템에 대한 이해를 위한 융합분석의 중요성이 점점 커지고 있다. 하나의 연구대상을 다양한 관점에서 관찰하여 얻게 되는 여러 데이터의 융합분석은 통해 좀 더 대상에 대한 깊은 이해를 가능하게 한다. 본 연구에서는 그중에서도 특히 하나의 샘플에서 두개의 고차원 데이터가 생성된 경우 다룰 수 있는 분석인 공관성분석과 정준상관분석을 비교하였다. 정준상관분석의 경우 고차원 데이터를 다룰 수 없는 단점이 있기에, 해당 문제를 극복하기 위하여 능형상수를 이용하는 방법(CCA-ridge)과 각 데이터의 공분산행렬을 항등행렬로 가정하여 벌점화 특이값분해를 이용한 방법(CCA-PMD) 두 가지를 고려하였으며 각 방법을 NCI60 세포주 패널에서 얻은 RNA 시퀀싱 데이터와 단백질 시퀀싱 데이터 분석에 적용하였다. 그 결과 정준상관분석의 경우 두 정준변수간의 상관관계에 좀 더 집중하는 반면 공관성분석은 각 데이터의 선형조합간의 상관관계뿐 아니라 각 선형조합의 변동성을 함께 고려함을 확인할 수 있었다. 또한 공관성분석의 경우 여러가지의 가중치행렬을 고려하여 그 결과값을 비교하고 중요 시사점을 도출하였다.

ASRP자료를 이용한 155MM 추진장약 KM4A2 저장수명 추정 연구 (A Study on the Estimation of Shelf-life for 155mm propelling charge KM4A2 using ASRP's data)

  • 윤근식;박상원
    • 품질경영학회지
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    • 제42권3호
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    • pp.291-300
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    • 2014
  • Purpose: The purpose of this study is to provide a statistical method from the data of ASRP's results and to apply to the reliability assessment of 155mm propelling charge, KM4A2. Methods: The accumulated data through ASRP for 155mm propelling charge were analyzed using regression analysis and MINITAB reliability analysis. The analysis methods used for this study were applied to statistical data types such as continuous data, binominal data. Results: The results of this study are as follows; The failure of 155mm propelling charge is mainly due to the broken charge bag, the decline of stabilizer content. The shelf-life(B5) regarding broken charge bag is 21.1years. The stabilizer content decrease with 0.0227%/year and safety storage period of propellant is 34.6years. Conclusion: The shelf-life of 155mm propelling charge determined by charge bag is estimated 21.1years.

A Trend Analysis of Floral Products and Services Using Big Data of Social Networking Services

  • Park, Sin Young;Oh, Wook
    • 인간식물환경학회지
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    • 제22권5호
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    • pp.455-466
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    • 2019
  • This study was carried out to analyze trends in floral products and services through the big data analysis of various social networking services (SNSs) and then to provide objective marketing directions for the floricultural industry. To analyze the big data of SNSs, we used four analytical methods: Cotton Trend (Social Matrix), Naver Big Data Lab, Instagram Big Data Analysis, and YouTube Big Data Analysis. The results of the big data analysis showed that SNS users paid positive attention to flower one-day classes that can satisfy their needs for direct experiences. Consumers of floral products and services had their favorite designs in mind and purchased floral products very actively. The demand for flower items such as bouquets, wreaths, flower baskets, large bouquets, orchids, flower boxes, wedding bouquets, and potted plants was very high, and cut flowers such as roses, tulips, and freesia were most popular as of June 1, 2019. By gender of consumers, females (68%) purchased more flower products through SNSs than males (32%). Consumers preferred mobile devices (90%) for online access compared to personal computers (PCs; 10%) and frequently searched flower-related words from February to May for the past three years from 2016 to 2018. In the aspect of design, they preferred natural style to formal style. In conclusion, future marketing activities in the floricultural industry need to be focused on social networks based on the results of big data analysis of popular SNSs. Florists need to provide consumers with the floricultural products and services that meet the trends and to blend them with their own sensitivity. It is also needed to select SNS media suitable for each gender and age group and to apply effective marketing methods to each target.

Analysis of the Effect of Wind Direction on Ozone Level

  • Na, Jong-Hwa;Sung, Su-Jin;Yu, Hye-Kyung
    • Communications for Statistical Applications and Methods
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    • 제19권4호
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    • pp.527-536
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    • 2012
  • In this paper we analyze the effect of circular variables such as wind direction, time and month on the ozone level. In particular, we examined the effect of wind direction by exploratory data analysis methods and provide the correlation and regression analyzes in the cases including all circular explanatory variables. In the analysis, we convert time and month variables to circular variables and analyze the effect of these variables on regression analysis; in addition, we also consider circular-circular regression. We used weather condition and air pollution data collected from Dongdaemoon district of Seoul in 2007.

석면노출연구를 위한 공간분석기법 (Spatial Analysis Methods for Asbestos Exposure Research)

  • 김주영;강동묵
    • 한국환경보건학회지
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    • 제38권5호
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    • pp.369-379
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    • 2012
  • Objectives: Spatial analysis is useful for understanding complicated causal relationships. This paper focuses trends and appling methods for spatial analysis associated with environmental asbestos exposure. Methods: Literature review and reflection of experience of authors were conducted to know academic background of spatial analysis, appling methods on epidemiology and asbestos exposure. Results: Spatial analysis based on spatial autocorrelation provides a variety of methods through which to conduct mapping, cluster analysis, diffusion, interpolation, and identification. Cause of disease occurrence can be investigated through spatial analysis. Appropriate methods can be applied according to contagiousness and continuity. Spatial analysis for asbestos exposure source is needed to study asbestos related diseases. Although a great amount of research has used spatial analysis to study exposure assessment and distribution of disease occurrence, these studies tend to focus on the construction of a thematic map without different forms of analysis. Recently, spatial analysis has been advanced by merging with web tools, mobile computing, statistical packages, social network analysis, and big data. Conclusions: Because the trend in spatial analysis has evolved from simple marking into a variety of forms of analyses, environmental researchers including asbestos exposure study are required to be aware of recent trends.

A Two Sample Test for Functional Data

  • Lee, Jong Soo;Cox, Dennis D.;Follen, Michele
    • Communications for Statistical Applications and Methods
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    • 제22권2호
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    • pp.121-135
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    • 2015
  • We consider testing equality of mean functions from two samples of functional data. A novel test based on the adaptive Neyman methodology applied to the Hotelling's T-squared statistic is proposed. Under the enlarged null hypothesis that the distributions of the two populations are the same, randomization methods are proposed to find a null distribution which gives accurate significance levels. An extensive simulation study is presented which shows that the proposed test works very well in comparison with several other methods under a variety of alternatives and is one of the best methods for all alternatives, whereas the other methods all show weak power at some alternatives. An application to a real-world data set demonstrates the applicability of the method.

규칙기반 및 상관분석 방법을 이용한 시계열 계측 데이터의 이상치 판정 (Outlier Detection in Time Series Monitoring Datasets using Rule Based and Correlation Analysis Method)

  • 전제성;구자갑;박창목
    • 한국지반환경공학회 논문집
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    • 제16권5호
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    • pp.43-53
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    • 2015
  • 본 연구에서는 빅데이터 범주에 포함되는 각종 계측 데이터를 대상으로 각종 이상치를 판단하기 위한 기법을 고안하고, 인공 데이터 및 실 계측 데이터를 이용한 이상치 분석을 수행하였다. 계측결과에 대한 1차 차분 값 및 오차율을 적용한 규칙기반 방법은 큰 규모의 Short fault 분석 및 일정 기간 계측값에 변화가 발생하지 않는 경우의 Constant fault 분석에 효과적으로 적용될 수 있었으나, 독립적인 단일 데이터셋만을 이용하는 관계로 큰 변화폭을 보이는 실 계측 데이터의 정상 데이터를 이상치로 오판하는 문제점이 있었다. 규칙기반 방법을 이용한 Noise fault 분석은 적정 데이터 윈도우 사이즈의 선택 및 이상치 판정용 한계값 선정상의 문제로 인해 실 계측 데이터 적용에 한계가 있었다. 이종 데이터 간 상관분석 방법은 학습 데이터의 적정범위 선정이 선행된다면 장단기 계측 데이터의 이상 거동 및 국부적 이상치 판정에 매우 효과적으로 이용될 수 있음을 알 수 있었다.