• 제목/요약/키워드: Statistical correlation analysis

검색결과 2,998건 처리시간 0.031초

산업재해 사례인자의 범주형 분석 (Categorical Analysis for the Factors of Incustrial Accident Cases)

  • 지경택;송영호;정국삼
    • 한국안전학회지
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    • 제17권1호
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    • pp.94-98
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    • 2002
  • This study aimed to search for the fundamental accident causes using a categorical analysis, a kind of statistical methods. As the analysis methods, correlation analysis, independence test and logistic regression analysis were used. And the SPSS package, a general-purpose mathematical library, was used to obtain statistical characteristics. As the result of this study, the accident causes associated with factor of 'lost working days' were factors such as 'employed periods', 'sex', 'type of accident', 'month'. In case of applying independence test method, the most important cause was the factor of 'month'. In case that logistic regression analysis method was applied, the cause contributed to the increase structure'. 'less than 6 month'. On the basis of these results, the plan for accident prevention and the proper investment for accident prevention expenditure could be carried out in each workshop.

Classification via principal differential analysis

  • Jang, Eunseong;Lim, Yaeji
    • Communications for Statistical Applications and Methods
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    • 제28권2호
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    • pp.135-150
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    • 2021
  • We propose principal differential analysis based classification methods. Computations of squared multiple correlation function (RSQ) and principal differential analysis (PDA) scores are reviewed; in addition, we combine principal differential analysis results with the logistic regression for binary classification. In the numerical study, we compare the principal differential analysis based classification methods with functional principal component analysis based classification. Various scenarios are considered in a simulation study, and principal differential analysis based classification methods classify the functional data well. Gene expression data is considered for real data analysis. We observe that the PDA score based method also performs well.

대구지역 부유분진중 Polycyclic Aromatic Hydrocarbons의 발생원 특성 (source Characteristics of Polycyclic Aromatic Hydrocarbons of Airborne Particulate Matter in Taegu Area)

  • 최성우;윤성훈
    • 한국환경보건학회지
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    • 제26권2호
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    • pp.34-40
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    • 2000
  • The purpose of this study was to investigate the seasonal variation of PAHs and to estimate their source characteristics in Taegu area. To do this, four sampling sites were selected to represent an industrial, a traffic, a traffic & residential, and a residential area in Taegu. Total of 72 samples had been collected from January, 1999 to September, 1999 on glass micro fiber filters by high volume air sampler. The PAHs in the total suspended particulate were extracted by a soxhlet process with dichloromethane and analyzed by GC/MSD, GC/FID. A statistical analysis was performed for the PAHs data set using a principal component analysis to derive important factor inherent in the interactions among the variables. The specific conclusions of this research are: 1) There was a significant seasonal and local variation in the atmospheric concentration of PAHs. The seasonal variation is winter>spring>Fall>summer, and the local variation is industrial>traffic>graffic & residential>residential area. 2) To evaluate the correlation between a measured PAHs and other affecting factors such as air pollutant concentration and meterological data, statistical analysis was performed. PAHs and other affecting factors such as air pollutant concentration and meterological data, statistical analysis was performed. PAHs have negative correlation with temperature (r=-0.593, p<0.05), radiation(r=-0.535, p<0.05), and O3(r=-0.719, p<0.05), but have positive correlation with NO(r=0.615, p<0.05) 3)Finally, multivariate analysis was performed for the PAHs dat set to identify and to estimate the source contributions of PAHs. According to results of statistical analysis, it could be identifies as three factors such as vehicular/gasoline, vehicular/diesel, and combustion in Taegu area.

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스트레이트 스커트의 여유분에 관한 연구 (A Study on Ease of Skirt)

  • 이소영;최혜선
    • 한국의류학회지
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    • 제21권8호
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    • pp.1275-1286
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    • 1997
  • The purpose of this study is to investigate how the shape of the lower body influences an individuals' ease in fitting skirts. Subjects in this study consisted of 188 adult females categorized into two groups(the first group were subjects 18∼33 years of age and the second group 34∼59 years of age), whose measurements were taken and then compared between the two groups. The subjects were also categorized into 5 different lower body types. The following are the results; (1) The comparative analysis of the ease from the two a9e groups showed a bigger value of waist girth in the young age group. And thereverse results were found when measuring hip firth. (2) The correlation analysis between the ease and the anthropometric data showed a weak statistical correlation in the older group, and showed no statistical correlation in the younger group. However, there was correlation between the ease and the body measurements as well as between the differences of waist girth and hip girth. (3) The most appropriate average ease of skirt in the young age group was 1.03 cm for waist and 5.71 cm for hip; the most appropriate average ease of skirt in the older age group was -0.76 cm at the waist and 4.10 cm at the hip. (4) Analysis of variance with a special emphasis on the ease of waist girth and hip girth according to the anthropometric data of the lower body revealed a statistically significant correlation.

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Exploring COVID-19 in mainland China during the lockdown of Wuhan via functional data analysis

  • Li, Xing;Zhang, Panpan;Feng, Qunqiang
    • Communications for Statistical Applications and Methods
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    • 제29권1호
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    • pp.103-125
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    • 2022
  • In this paper, we analyze the time series data of the case and death counts of COVID-19 that broke out in China in December, 2019. The study period is during the lockdown of Wuhan. We exploit functional data analysis methods to analyze the collected time series data. The analysis is divided into three parts. First, the functional principal component analysis is conducted to investigate the modes of variation. Second, we carry out the functional canonical correlation analysis to explore the relationship between confirmed and death cases. Finally, we utilize a clustering method based on the Expectation-Maximization (EM) algorithm to run the cluster analysis on the counts of confirmed cases, where the number of clusters is determined via a cross-validation approach. Besides, we compare the clustering results with some migration data available to the public.

통계적인 기법을 활용한 동질성구간에 따른 교통량 수시조사 효율화 연구 (Determination of a Homogeneous Segment for Short-term Traffic Count Efficiency Using a Statistical Approach)

  • 정유석;오주삼
    • 한국도로학회논문집
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    • 제17권4호
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    • pp.135-141
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    • 2015
  • PURPOSES: This study has been conducted to determine a homogeneous segment and integration to improve the efficiency of short-term traffic count. We have also attempted to reduce the traffic monitoring budget. METHODS: Based on the statistical approach, a homogeneous segment in the same road section is determined. Statistical analysis using t-test, mean difference, and correlation coefficient are carried out for 10-year-long (2004-2013) short-term count traffic data and the MAPE of fresh data (2014) are evaluated. The correlation coefficient represents a trend in traffic count, while the mean difference and t-score represent an average traffic count. RESULTS : The statistical analysis suggests that the number of target segments varies with the criteria. The correlation coefficient of more than 30% of the adjacent segment is higher than 0.8. A mean difference of 36.2% and t-score of 19.5% for adjacent segments are below 20% and 2.8, respectively. According to the effectiveness analysis, the integration criteria of the mean difference have a higher effect as compared to the t-score criteria. Thus, the mean difference represents a traffic volume similarity. CONCLUSIONS : The integration of 47 road segments from 882 adjacent road segments indicate 8.87% of MAPE, which is within an acceptable range. It can reduce the traffic monitoring budget and increase the count to improve an accuracy of traffic volume estimation.

생체(生體)리듬이 작업성과(作業成果)에 미치는 영향(影響) (The Effect of Biorhythm to Work Performance)

  • 박은희;이상용
    • 대한인간공학회지
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    • 제5권1호
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    • pp.43-48
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    • 1986
  • This study aims to investigate the effect of biorhythm to work performance. In order to do this, the data are collected from the manufacturing factory which produce a sportware, and the statistical test are made to testify the relationship between the number of defective items and the biorhythm chart of the workers. The number of defective items which made in the peak day, usual day, and critical day on the worker's biorythm chart are compared with each other, and the statistical test are made to see if there are difference between them, and the correlation analysis are made to see if there is any correlation between the work performance and the biorhythm chart. The result of the statistical test shows that the biorythm of the worker gives an effect to his work performance with a correlation.

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Statistical Analysis of Fluorescence Correlation Spectroscopy of Ultra Low Concentration Molecules with a Confocal Microscope

  • Lee, Soon-Hyouk;Lim, Gyu-Chang;Kim, Soo-Yong;Kim, Eun-Kyung;Kim, Hak-Sung;Kim, Sok-Won
    • Journal of the Optical Society of Korea
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    • 제12권3호
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    • pp.170-173
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    • 2008
  • In this study, we simulated a statistical model of FCS(fluorescence correlation spectroscopy) based on a Poisson process to understand and explain observations of the experiment performed on molecules of ultra-low concentration by the home-built laser-scanning confocal microscope. The statistical model confirmed that the relative mean square amplitude of fluctuations is shown to be inversely proportional to the average number of molecules, even in the ultra-low concentration, if some conditions are satisfied. Signal-to-noise ratio and the variability of dwelling time under the confocal volume were found to be effective conditions for the experiment.

A precise sensor fault detection technique using statistical techniques for wireless body area networks

  • Nair, Smrithy Girijakumari Sreekantan;Balakrishnan, Ramadoss
    • ETRI Journal
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    • 제43권1호
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    • pp.31-39
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    • 2021
  • One of the major challenges in wireless body area networks (WBANs) is sensor fault detection. This paper reports a method for the precise identification of faulty sensors, which should help users identify true medical conditions and reduce the rate of false alarms, thereby improving the quality of services offered by WBANs. The proposed sensor fault detection (SFD) algorithm is based on Pearson correlation coefficients and simple statistical methods. The proposed method identifies strongly correlated parameters using Pearson correlation coefficients, and the proposed SFD algorithm detects faulty sensors. We validated the proposed SFD algorithm using two datasets from the Multiparameter Intelligent Monitoring in Intensive Care database and compared the results to those of existing methods. The time complexity of the proposed algorithm was also compared to that of existing methods. The proposed algorithm achieved high detection rates and low false alarm rates with accuracies of 97.23% and 93.99% for Dataset 1 and Dataset 2, respectively.

Correlation analysis and time series analysis of Ground-water inflow rate into tunnel of Seoul subway system

  • 김성준;이강근;염병우
    • 한국지하수토양환경학회:학술대회논문집
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    • 한국지하수토양환경학회 2003년도 추계학술발표회
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    • pp.254-257
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    • 2003
  • Statistical analysis is performed to estimate the correlations between geological or geographical factor and groundwater inflow rates in the Seoul subway system. Correlation analysis shows that among several geological and geographical factors fractures and streams have most strong effects on inflow rate into tunnels. In particular, subway line 5∼8 are affected more by these factors than subway line 1∼4. Time series analysis is carried out to forecast groundwater inflow rate. Time series analysis is a useful empirical method for simulation and forecasts in case that physical model can not be applied to. The time series of groundwater inflow rates is calculated using the observation data. Transfer function-noise model is applied with the precipitation data as input variables. For time series analysis, statistical methods are performed to identify proper model and autoregressive-moving average models are applied to evaluation of inflow rate. Each model is identified to satisfy the lowest value of information criteria. Results show that the values by result equations are well fitted with the actual inflow rate values. The selected models could give a good explanation of inflow rates variation into subway tunnels.

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