• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.5
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• pp.253-263
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• 2021

Traffic data collected using advanced equipment are highly valuable for traffic planning and efficient road operation. However, there is a problem regarding the reliability of the analysis results due to equipment defects, errors in the data aggregation process, and missing data. Unlike other detectors installed for each vehicle lane, radar detectors can yield different error types because they detect all traffic volume in multilane two-way roads via a single installation external to the roadway. For the traffic data of a radar detector to be representative of reliable data, the error factors of the radar detector must be analyzed. This study presents a field survey of variables that may cause errors in traffic volume collection by targeting the points where radar detectors are installed. Video traffic data are used to determine the errors in traffic measured by a radar detector. This study establishes three types of radar detector traffic errors, i.e., artificial, mechanical, and complex errors. Among these types, it is difficult to determine the cause of the errors due to several complex factors. To solve this problem, this study developed a radar detector traffic volume error analysis model using a multiple linear regression model. The results indicate that the characteristics of the detector, road facilities, geometry, and other traffic environment factors affect errors in traffic volume detection.

• The Korean Journal of Applied Statistics
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• v.34 no.4
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• pp.589-597
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• 2021

In simple and multiple regression, there is a difference in the meaning of regression coefficients, and not only are the estimates of regression coefficients different, but they also have different signs. Understanding the relative contribution of explanatory variables in a regression model is an important part of regression analysis. In a standardized regression model, the regression coefficient can be interpreted as the change in the response variable with respect to the standard deviation when the explanatory variable increases by the standard deviation in a situation where the values of the explanatory variables other than the corresponding explanatory variable are fixed. However, the size of the standardized regression coefficient is not a proper measure of the relative importance of each explanatory variable. In this paper, the estimator of the regression coefficient in multiple regression is expressed as a function of the correlation coefficient and the coefficient of determination. Furthermore, it is considered in terms of the effect of an additional explanatory variable and additional increase in the coefficient of determination. We also explore the relationship between estimates of regression coefficients and correlation coefficients in various plots. These results are specifically applied when there are two explanatory variables.

• Water for future
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• v.6 no.2
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• pp.6-11
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• 1973

This paper include the hydrometeorological analyses of evapotranspiration which is import factor concerning the estimate of water budgest over a certain basin. Evapotranspiration model mode by the multiple regression analysis between the evapotranspiration measured on various kinds of ground cover (water, bare soil and lawn) and the other meteorological elements affecting the evapotranspiration process, and the simple regression analysis between the evapo transpiration measured on each ground cover and the evapotranspiration on water and vegetables calculated from the Penman equation. It is expected that the evapotranspiration models are a very useful formulae estimating ten days amounts or a month's amounts.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.1
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• pp.117-124
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• 2015

This study explored the determinant variables of physical health of the high school students in Korea. Specifically, it explored how the sociodemographic characteristics factor, school factor, delinquent behaviors factor of the students affect their physical health using the 2012 Korean Youth Health Risk Behavior On-line Survey. Using the case of 36,889, this study conducted frequency analysis, t-test, F-test, and multiple regression analysis. As the result of total multiple regression analysis, gender, father's educational level, sibling(s), economic status, grade, academic record, problem drinking, drug use were statistically significant determinant variables of physical health of the high school students in Korea. Also, it delivered some implications for enhancing their physical health.

• Journal of the Korean Data and Information Science Society
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• v.20 no.4
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• pp.713-717
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• 2009

The purpose of this paper is to analyse the factors influencing satisfaction, reliance, and loyalty to the life insurance companies. The factors are divided into two categories: the characteristics of life insurance companies and sellers. Factor analysis and multiple regression is employed. Two factors are found in the analysis of the characteristics of life insurance companies. Those are quality and social liability of life insurance companies. One factor are extracted from the analysis of the characteristics of sellers. We also find each one factor in the factor analysis of satisfaction, reliance, and loyalty. The findings are summarized as follows. Firstly, the role of sellers are very important for the three performance variables, namely satisfaction, reliance, and loyalty. Secondly, the factor for social liability of life insurance companies is statistically significant to the satisfaction performance. Finally, The three explaining variables are statistically significant to the reliance and loyalty performance.

• International Journal of Computer Science & Network Security
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• v.23 no.9
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• pp.37-46
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• 2023

The main aim of the article is to solve the problem of automating price monitoring using marketing forecasting methods and Excel functionality under martial law. The study used the method of algorithms, trend analysis, correlation and regression analysis, ANOVA, extrapolation, index method, etc. The importance of monitoring consumer price developments in market pricing at the macro and micro levels is proved. The introduction of a Dummy variable to account for the influence of martial law in market pricing is proposed, both in linear multiple regression modelling and in forecasting the components of the Consumer Price Index. Experimentally, the high reliability of forecasting based on a five-factor linear regression model with a Dummy variable was proved in comparison with a linear trend equation and a four-factor linear regression model. Pessimistic, realistic and optimistic scenarios were developed for forecasting the Consumer Price Index for the situation of the end of the Russian-Ukrainian war until the end of 2023 and separately until the end of 2024.

• Journal of the Korean Society of Clothing and Textiles
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• v.25 no.2
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• pp.358-365
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• 2001

The purpose of this study was to investigate the relation between various aspects of multiple body image and clothing behavior i.e. individuality/self expression, body improvement, social approval, sex appeal. The data were collected from 498 female university students in Seoul and Kyong Ki Province and analyzed using factor analysis, Pearsons correlations, reliability test, analysis of variance, and multiple regression analysis. The results of this study were as follows: 1) Four dimensions of multiple body image were identified : appearance, body attractiveness, degree of fitness and atheletic skill. 2) Perception on appearance and fitness aspect of multiple body image has a positive correlation with all aspects of clothing behavior i.e. individuality/self expression, body improvement, social approval and sex appeal of clothing behavior. Body attractiveness and atheletic skill of multiple body image also had a positive correlation with individuality/self expression, and sex appeal.

• Korean Journal of Hospice Care
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• v.6 no.2
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• pp.69-78
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• 2006

Purpose: This study was conducted to analysis relationship about quality of life and family burden of the home-based hospice patient families. Method: The subjects consisted of 94 families with home-based hospice patient. The ages of the subjects were 17-73 years with hospice patient who receivedhome visiting care and registered at 4 hospitals in Daegu and Kyung-Buk. The data was collected from March to November 2004. The instruments used for the study were Quality of Life Scale (GLS) and Family Burden Questionnaire (FBQ). The analysis was done using frequency, mean, standard deviation, correlation and stepwise multiple regression with SPSS WIN 11.0. Results: The results were as follows: 1. The mean score of family burden was 3.36 ($\pm0.55$). The highest mean score of family burden 6 factors were wellness of future 3.85($\pm1.10$), and the second was economic family burden 3.63($\pm0.97$). 2. The mean score of quality of life was 3.09 ($\pm0.48$). The lowest score of quality of life 6 factors were economic status 2.86($\pm0.54$), and the second was physical state and function 3.01($\pm0.62$). 3. In the home-based hospice patient families, family burden had significant negative correlation with quality of life(r=-0.25, p=0.012). 4. Emotional status accounted for 11% of family burden in the home-based hospice patient families by means of stepwise multiple regression. 5. Economical status accounted for 18 and age accounted for an additional 11% of quality of life in the home-based hospice patient families by means of stepwise multiple regression. Conclusion: The finding showed that family burden and quality of life of home-based hospice patient families were significantly negative correlation and the highest factor of family burden was wellness of future and the most important factor of quality of life was economic status.

• Water for future
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• v.17 no.2
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• pp.107-112
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• 1984

It si presented here that in order to estimate reservoir sedimentation rate through the use of reservoir survey data of 66 irrigation reservoir in 3 major watersheds in this country, the correlation between reservoir sedimentation rate and the following factors; watershed area, trap-efficiency, watershed slope, shape factor of water shed, and reservoir deposition age in two models simple regression model and multiple regression model. Appropriatness of the proposed models have been calibrated from the survey data and as a result, it has been determined that the multiple regression model is much more accurate than the simple regression model. The annual sediment yield is correlated with watershed area and reservoir trap efficiency. It has been found that variation of the annual average sedimentation rate and the annual reservoir capacity loss rate are influenced by the trap efficiency of reservoir.

• Journal of Korea Water Resources Association
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• v.42 no.6
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• pp.465-480
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• 2009

In this study, single and multiple linear regression model were used to derive the relationship between precipitation and altitude, latitude and longitude in Jejudo. The single linear regression analysis was focused on whether orographic effect was existed in Jejudo by annual average precipitation, and the multiple linear regression analysis on whether orographic effect was applied to each duration and return period of quantile from regional frequency analysis by index flood method. As results of the regression analysis, it shows the relationship between altitude and precipitation strongly form a linear relationship as the length of duration and return period increase. The multiple linear regression precipitation estimates(which used altitude, latitude, and longitude information) were found to be more reasonable than estimates obtained using altitude only or altitude-latitude and altitude-longitude. Especially, as results of spatial distribution analysis by kriging method using GIS, it also provides realistic estimates for precipitation that the precipitation was occurred the southeast region as real climate of Jejudo. However, the accuracy of regression model was decrease which derived a short duration of precipitation or estimated high region precipitation even had long duration. Consequently the other factor caused orographic effect would be needed to estimate precipitation to improve accuracy.