• 한국대기환경학회지
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• 제27권6호
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• pp.650-662
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• 2011

The statistical tools such as empirical orthogonal function (EOF), and singular value decomposition (SVD) have been applied to analyze the characteristic of air pollutant over southeast Asia as well as to evaluate Zimeke's tropospheric column ozone (ZTO) determined by tropospheric residual method. In this study, we found that the EOF and SVD analyses are useful methods to extract the most significant temporal and spatial pattern from enormous amounts of satellite data. The EOF analyses with OMI $NO_2$ and OMI HCHO over southeast Asia revealed that the spatial pattern showed high correlation with fire count (r=0.8) and the EOF analysis of CO (r=0.7). This suggests that biomass burning influences a major seasonal variability on $NO_2$ and HCHO over this region. The EOF analysis of ZTO has indicated that the location of maximum ZTO was considerably shifted westward from the location of maximum of fire count and maximum month of ZTO occurred a month later than maximum month (March) of $NO_2$, HCHO and CO. For further analyses, we have performed the SVD analyses between ZTO and ozone precursor to examine their correlation and to check temporal and spatial consistency between two variables. The spatial pattern of ZTO showed latitudinal gradient that could result from latitudinal gradient of stratospheric ozone and temporal maximum of ZTO in March appears to be associated with stratospheric ozone variability that shows maximum in March. These results suggest that there are some sources of error in the tropospheric residual method associated with cloud height error, low efficiency of tropospheric ozone, and low accuracy in lower stratospheric ozone.

• 기술혁신학회지
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• 제9권4호
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• pp.842-864
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• 2006

본 연구는 상장기업 311개 업체를 표본으로 하여 독립변수인 상장 이전 연구개발비에 대해 종속 변수인 상장 이후 기업 성과에 미치는 영향을 회귀분석을 통하여 실증 분석하였다. 연구결과는 다음과 같다. 첫째, IPO 직전년도 연구개발비는 IPO 당해년도 기업 성과인 평균 시가총액/자산은 모든 모형에서 유의한 양(+)의 상관관계를 미치고 있고, 평균 주가에는 모든 모형에서 유의한 결과를 보이지 않았으나 양(+)의 결과를 보였다. 또한 연구개발비 지출에 대한 매출액과 주당 순 자산의 변화는 통계적으로 유의하지 않는 것으로 나타났다. 둘째, IPO 이전 3년 평균 연구개발비에 대한 IPO 당해포함 이후 3년 평균 기업성과는 평균시가 총액/자산에는 모든 모형에서 유의한 양(+)의 결과를 보였다. 평균 주가에 자산화 된 연구개발비에 따른 평균 주가 변동은 유의한 양(+)의 결과를 보였고 비용 화된 연구개발비의 경우는 유의한 음(-)의 영향을 미치고 있다. 이러한 결과는 기업들의 연구개발비에 따른 신호효과(singnal effect)로 인한 주가에 미치는 영향은 단기 혹은 중장기(3-5년)에 긍정적으로 나타나는 것으로 추정되나 원초적으로 기술 수준이 낮은 벤처 및 일반기업 등은 연구개발비가 기업성과에 단기적으로 수익성 제고에 부정적인 영향을 미치는 것으로 해석된다.

• 한국약용작물학회지
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• 제24권2호
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• pp.93-100
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• 2016

Background: A set of logical criteria that can accurately identify and verify the cultivation region of raw materials is a critical tool for the scientific management of traditional herbal medicine. Methods and Results: Volatile compounds were obtained from 19 and 32 samples of Angelica gigas Nakai cultivated in Korea and China, respectively, by using steam distillation extraction. The metabolites were identified using GC/MS by querying against the NIST reference library. Data binning was performed to normalize the number of variables used in statistical analysis. Multivariate statistical analyses, such as Principal Component Analysis (PCA), Partial Least Squares-Discriminant Analysis (PLS-DA), and Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) were performed using the SIMCA-P software. Significant variables with a Variable Importance in the Projection (VIP) score higher than 1.0 as obtained through OPLS-DA and those that resulted in p-values less than 0.05 through one-way ANOVA were selected to verify the marker compounds. Among the 19 variables extracted, styrene, ${\alpha}$-pinene, and ${\beta}$-terpinene were selected as markers to indicate the origin of A. gigas. Conclusions: The statistical model developed was suitable for determination of the geographical origin of A. gigas. The cultivation regions of six Korean and eight Chinese A. gigas. samples were predicted using the established OPLS-DA model and it was confirmed that 13 of the 14 samples were accurately classified.

• 한국산업정보학회논문지
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• 제15권1호
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• pp.109-114
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• 2010

본 논문에서는 통계패키지와 Active Server Page(ASP)를 이용하여 통계분석을 위한 웹 컨텐츠를 개발하였다. 통계패키지는 통계비전공자에게 사용하기도 어렵고 배우기도 매우 어렵지만, 통계비전공자들은 SAS, S-plus, R 등과 같은 통계패키지에 대한 학습 없이 자료를 분석하기를 원하고 있다. 따라서 본 연구에서는 통계패키지로 많이 활용되고 있는 S-plus와 ASP를 이용하여 통계분석 웹 컨텐츠를 개발하였다. 실제 응용으로, 수질오염자료에 대하여 웹 상에서 탐색적 자료 분석, 분산분석, 시계열 분석 등과 같은 다양한 분석에 대한 웹 컨텐츠를 개발하였다. 개발된 웹 통계분석은 공무원, 연구원 등과 같은 통계 비전문가들에게 매우 유용한 도구이다. 결과적으로 웹 기반의 통계분석 컨텐츠를 통하여 인터넷으로 하여금 사용자들로 하여금 자료 분석을 쉽게 빠르게 할 수 있다.

• 대한음성학회지:말소리
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• 제55권
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• pp.45-60
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• 2005

The purpose of this paper is to represent values of acoustic cues for Korean oral stops in the multi-dimensional space, and to attempt to find possible relationships among acoustic cues through correlation analyses. The acoustic cues used for differentiation of 3 types of Korean stops are closure duration, voice onset time and fundamental frequency of a vowel after a stop. The values of these cues are plotted in the two and three dimensional space to see what the critical cues are for separation of different types of stops. Correlation coefficient analyses show that multi-variate approach to statistical analysis is legitimate, and that there are statistically significant relationships among acoustic cues but Oey are not strong enough to make the conjecture that there is a possible relationship among the articulatory or laryngeal mechanisms employed by the acoustic cues.

• 산업공학
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• 제12권3호
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• pp.448-457
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• 1999

Accelerated degradation is concerned with models and data analyses for degradation of product performance over time at overstress and design conditions. Although there have been numerous studies with accelerated degradation theory in reliability, very few actually apply to parametric statistical analyses. This paper shows how to analyze degradation data, provides tests for how well the assumptions hold. Reel sensors, a sort of photointerrupters in home VCR, hive been tested, and least-square analyses are used to illustrate our approach. Tests for linearity of the performance-time relationship, dependence of the lognormal distribution, and the standard deviation on time are performed. The mean life of tested sensors is assessed at about 414,000 hours, and the Arrhenius activation energy of this reaction is concluded to be 0.39 eV as results.

• Restorative Dentistry and Endodontics
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• 제49권2호
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• pp.21.1-21.8
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• 2024

Objectives: This paper aims to serve as a useful guide for sample size determination for various correlation analyses that are based on effect sizes and confidence interval width. Materials and Methods: Sample size determinations are calculated for Pearson's correlation, Spearman's rank correlation, and Kendall's Tau-b correlation. Examples of sample size statements and their justification are also included. Results: Using the same effect sizes, there are differences between the sample size determination of the 3 statistical tests. Based on an empirical calculation, a minimum sample size of 149 is usually adequate for performing both parametric and non-parametric correlation analysis to determine at least a moderate to an excellent degree of correlation with acceptable confidence interval width. Conclusions: Determining data assumption(s) is one of the challenges to offering a valid technique to estimate the required sample size for correlation analyses. Sample size tables are provided and these will help researchers to estimate a minimum sample size requirement based on correlation analyses.

• 천문학회지
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• 제40권4호
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• pp.99-106
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• 2007

Statistical analyses were performed to investigate the relative success and accuracy of daily maximum X-ray flux (MXF) predictions, using both multilinear regression and autoregressive time-series prediction methods. As input data for this work, we used 14 solar activity parameters recorded over the prior 2 year period (1989-1990) during the solar maximum of cycle 22. We applied the multilinear regression method to the following three groups: all 14 variables (G1), the 2 so-called 'cause' variables (sunspot complexity and sunspot group area) showing the highest correlations with MXF (G2), and the 2 'effect' variables (previous day MXF and the number of flares stronger than C4 class) showing the highest correlations with MXF (G3). For the advanced three days forecast, we applied the autoregressive timeseries method to the MXF data (GT). We compared the statistical results of these groups for 1991 data, using several statistical measures obtained from a $2{\times}2$ contingency table for forecasted versus observed events. As a result, we found that the statistical results of G1 and G3 are nearly the same each other and the 'effect' variables (G3) are more reliable predictors than the 'cause' variables. It is also found that while the statistical results of GT are a little worse than those of G1 for relatively weak flares, they are comparable to each other for strong flares. In general, all statistical measures show good predictions from all groups, provided that the flares are weaker than about M5 class; stronger flares rapidly become difficult to predict well, which is probably due to statistical inaccuracies arising from their rarity. Our statistical results of all flares except for the X-class flares were confirmed by Yates' $X^2$ statistical significance tests, at the 99% confidence level. Based on our model testing, we recommend a practical strategy for solar X-ray flare predictions.

• 한국대기환경학회:학술대회논문집
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• 한국대기환경학회 2006년도 춘계학술대회 논문집
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• pp.366-367
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• 2006

• 대한간호학회지
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• 제45권5호
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• pp.641-649
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• 2015

Purpose: The purpose of this study was to introduce the main concepts of statistical testing and effect size and to provide researchers in nursing science with guidance on how to calculate the effect size for the statistical analysis methods mainly used in nursing. Methods: For t-test, analysis of variance, correlation analysis, regression analysis which are used frequently in nursing research, the generally accepted definitions of the effect size were explained. Results: Some formulae for calculating the effect size are described with several examples in nursing research. Furthermore, the authors present the required minimum sample size for each example utilizing G*Power 3 software that is the most widely used program for calculating sample size. Conclusion: It is noted that statistical significance testing and effect size measurement serve different purposes, and the reliance on only one side may be misleading. Some practical guidelines are recommended for combining statistical significance testing and effect size measure in order to make more balanced decisions in quantitative analyses.