• Title/Summary/Keyword: Regression analysis

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ALC(Autoclaved Lightweight Concrete) Hardness Prediction Research By Multiple Regression Analysis (다중회귀분석을 이용한 ALC 경도예측에 관한 연구)

  • Kim, Gwang-Su;Baek, Seung-Hun
    • Proceedings of the Safety Management and Science Conference
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    • 2012.04a
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    • pp.117-137
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    • 2012
  • In the ALC(Autoclaved lightweight concrete) manufacturing process, if the pre-cured semi-cake is removed after proper time is passed, it will be hard to retain the moisture and be easily cracked. Therefore, in this research, we took the research by multiple regression analysis to find relationship between variables for the prediction the hardness that is the control standard of the removal time. We study the relationship between Independent variables such as the V/T(Vibration Time), V/T movement, expansion height, curing time, placing temperature, Rising and C/S ratio and the Dependent variables, the hardness by multiple regression analysis. In this study, first, we calculated regression equation by the regression analysis, then we tried phased regression analysis, best subset regression analysis and residual analysis. At last, we could verify curing time, placing temperature, Rising and C/S ratio influence to the hardness by the estimated regression equation.

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Understanding of the Misuse Cases of Quantitative and Qualitative Regression Analysis (정량적, 정성적 회귀분석의 오적용과 이해)

  • Choe, Seong-Un
    • Proceedings of the Safety Management and Science Conference
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    • 2011.11a
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    • pp.213-217
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    • 2011
  • The research shows misuse cases of quantitative regression analysis used in QC circle activity and six sigma movement which presents guidelines of correct use for quality practitioners. Additionally, the qualitative regression analysis that responses nonconforming ratio of variable y, is reviewed based on misuse cases for proper use by practitioners in the field. In most cases, there are frequent errors that involve the correlation analysis or ANOVA, regardless of using quantitative regression analysis. In addition, qualitative regression analysis for the nonconforming ratio that has dependent variable of discrete and categorical data, is often applied with quantitative regression and result in ineffective quality improvement.

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On Logistic Regression Analysis Using Propensity Score Matching (성향점수매칭 방법을 사용한 로지스틱 회귀분석에 관한 연구)

  • Kim, So Youn;Baek, Jong Il
    • Journal of Applied Reliability
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    • v.16 no.4
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    • pp.323-330
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    • 2016
  • Purpose: Recently, propensity score matching method is used in a large number of research paper, nonetheless, there is no research using fitness test of before and after propensity score matching. Therefore, comparing fitness of before and after propensity score matching by logistic regression analysis using data from 'online survey of adolescent health' is the main significance of this research. Method: Data that has similar propensity in two groups is extracted by using propensity score matching then implement logistic regression analysis on before and after matching separately. Results: To test fitness of logistic regression analysis model, we use Model summary, -2Log Likelihood and Hosmer-Lomeshow methods. As a result, it is confirmed that the data after matching is more suitable for logistic regression analysis than data before matching. Conclusion: Therefore, better result which has appropriate fitness will be shown by using propensity score matching shows better result which has better fitness.

Multivariate Analysis for Clinicians (임상의를 위한 다변량 분석의 실제)

  • Oh, Joo Han;Chung, Seok Won
    • Clinics in Shoulder and Elbow
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    • v.16 no.1
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    • pp.63-72
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    • 2013
  • In medical research, multivariate analysis, especially multiple regression analysis, is used to analyze the influence of multiple variables on the result. Multiple regression analysis should include variables in the model and the problem of multi-collinearity as there are many variables as well as the basic assumption of regression analysis. The multiple regression model is expressed as the coefficient of determination, $R^2$ and the influence of independent variables on result as a regression coefficient, ${\beta}$. Multiple regression analysis can be divided into multiple linear regression analysis, multiple logistic regression analysis, and Cox regression analysis according to the type of dependent variables (continuous variable, categorical variable (binary logit), and state variable, respectively), and the influence of variables on the result is evaluated by regression coefficient${\beta}$, odds ratio, and hazard ratio, respectively. The knowledge of multivariate analysis enables clinicians to analyze the result accurately and to design the further research efficiently.

ALC(Autoclaved Lightweight Concrete) Hardness Prediction by Multiple Regression Analysis (다중회귀분석을 이용한 ALC 경도예측에 관한 연구)

  • Kim, Kwang-Soo;Baek, Seung-Hoon;Chung, Soon-Suk
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.7 no.2
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    • pp.101-111
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    • 2012
  • In the ALC(Autoclaved lightweight concrete) manufacturing process, if the pre-cured semi-cake is removed after proper time is passed, it will be hard to retain the moisture and be easily cracked. Therefore, in this research, we took the research by multiple regression analysis to find relationship between variables for the prediction the hardness that is the control standard of the removal time. We study the relationship between Independent variables such as the V/T(Vibration Time), V/T movement, expansion height, curing time, placing temperature, Rising and C/S ratio and the Dependent variables, the hardness by multiple regression analysis. In this study, first, we calculated regression equation by the regression analysis, then we tried phased regression analysis, best subset regression analysis and residual analysis. At last, we could verify curing time, placing temperature, Rising and C/S ratio influence to the hardness by the estimated regression equation.

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Vibration Analysis of Small Universial Motor by Regression Analysis (회귀분석을 이용한 소형 유니버셜 모터의 진동해석)

  • Cha, W.J.;Choi, Y.S.
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2002.11b
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    • pp.86-91
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    • 2002
  • The regression analysis in the six sigma process is used to reduce the vibration of an electric grinder. The vibration characteristics and the contribution of each part to overall vibration of the electric grinder is investigated through various vibration measurements and frequency analysis for the assembled and disassembled one. Then the application of the regression analysis finds out that the rotating components of the armature have more severe contributions to the overall vibration than the frequency components of the fan or the gear part, which is decided with higher value of the coefficient of determination. The unbalance and looseness of the armature and the fan are tested again by the regression analysis in order to decide how much unbalance or looseness should be reduced for the predetermined goal of vibration level of the electric grinder. These results show that the regression analysis can be a valuable tool in production line to decide where and how much faults needs to be adjusted for the reduction of vibration and noise.

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Analysis of the relationship between regulation compliance and occupational injuries - Focusing on logistic and poisson regression analysis - (규제 순응도와 산업재해 발생 수준간의 관계 분석 - 로지스틱 회귀분석과 포아송 회귀분석을 중심으로 -)

  • Rhee, Kyung-Yong;Kim, Ki-Sik;Yoon, Young-Shik
    • Journal of the Korea Safety Management & Science
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    • v.15 no.2
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    • pp.9-20
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    • 2013
  • OSHA(Occupational Safety and Health Act) generally regulates employer's business principles in the workplace to maintain safety environment. This act has the fundamental purpose to protect employee's safety and health in the workplace by reducing industrial accidents. Authors tried to investigate the correlation between 'occupational injuries and illnesses' and level of regulation compliance using Survey on Current Status of Occupational Safety & Health data by the various statistical methods, such as generalized regression analysis, logistic regression analysis and poison regression analysis in order to compare the results of those methods. The results have shown that the significant affecting compliance factors were different among those statistical methods. This means that specific interpretation should be considered based on each statistical method. In the future, relevant statistical technique will be developed considering the distribution type of occupational injuries.

The disparity profile of working conditions by the type of employment according to the economic sectors and occupations (임금근로자의 고용형태별 유해요인 노출 격차의 업종별 직종별 분포 특성)

  • Rhee, Kyung-Yong;Kim, Ki-Sik;Yoon, Young-Shik
    • Journal of the Korea Safety Management & Science
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    • v.15 no.4
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    • pp.197-207
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    • 2013
  • OSHA(Occupational Safety and Health Act) generally regulates employer's business principles in the workplace to maintain safety environment. This act has the fundamental purpose to protect employee's safety and health in the workplace by reducing industrial accidents. Authors tried to investigate the correlation between 'occupational injuries and illnesses' and level of regulation compliance using Survey on Current Status of Occupational Safety & Health data by the various statistical methods, such as generalized regression analysis, logistic regression analysis and poison regression analysis in order to compare the results of those methods. The results have shown that the significant affecting compliance factors were different among those statistical methods. This means that specific interpretation should be considered based on each statistical method. In the future, relevant statistical technique will be developed considering the distribution type of occupational injuries.

A Study on the Weight Estimation Model of Floating Offshore Structures using the Non-linear Regression Analysis (비선형 회귀 분석을 이용한 부유식 해양 구조물의 중량 추정 모델 연구)

  • Seo, Seong-Ho;Roh, Myung-Il;Shin, Hyunkyoung
    • Journal of the Society of Naval Architects of Korea
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    • v.51 no.6
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    • pp.530-538
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    • 2014
  • The weight estimation of floating offshore structures such as FPSO, TLP, semi-Submersibles, Floating Offshore Wind Turbines etc. in the preliminary design, is one of important measures of both construction cost and basic performance. Through both literature investigation and internet search, the weight data of floating offshore structures such as FPSO and TLP was collected. In this study, the weight estimation model was suggested for FPSO. The weight estimation model using non-linear regression analysis was established by fixing independent variables based on this data and the multiple regression analysis was introduced into the weight estimation model. Its reliability was within 4% of error rate.

Simplification of PMV through Multiple Regression Analysis (다중회귀분석을 통한 PMV 모델의 단순화)

  • Moon, Yong-Jun;Noh, Kwang-Chul;Oh, Myung-Do
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.19 no.11
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    • pp.761-769
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    • 2007
  • The purpose of this study is to present a simplified model of predicted mean vote (PMV) using multiple regression analysis. We performed the experiments and the numerical calculations in the lecture room during summer and winter to simplify PMV. And the multiple regression analysis on PMV was conducted to estimate the contribution of independent variables toward PMV. From the multiple regression analysis, we found that the effect of independent variables on PMV followed in order, clo value>air temperatur>air velocity>mean radiant temperature>relative humidity. And the simplified PMV was proposed through a few assumptions and then was compared with original PMV. They had a good agreement with each other. Additionally, we compared the simplified PMV with EDT. We expected that the simplified PMV can be more useful than EDT to evaluate the thermal comfort in the place, where radiation is dominant. But the comfort range of the simplified PMV should be adjusted to predict the exact thermal comfort in the future.