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

• Journal of Agricultural Extension & Community Development
• /
• v.18 no.3
• /
• pp.409-434
• /
• 2011

The main purpose of this study was to examine the effects of servicescape on post evaluation of hospitality industry in Gyeongnam. Customers of deluxe hotels in Gyeongnam were selected for a questionnaire survey. To achieve the study objective, 253 valid questionnaires were statistically analyzed, using frequency analysis, factor, reliability analysis and regression analysis. The results of the multiple regression analysis indicated that five of servicescape factors had significant impact on customer satisfaction and customer retention. The servicescape factors partially exerted a positive influence on word-of-mouth intention. The result of the simple regression analysis also indicated that the customer satisfaction had very significant impact on customer retention and word-of-mouth intention.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
• /
• 2001.11a
• /
• pp.199-202
• /
• 2001

This paper presents the correlation on the contamination degree and weather conditions using the multiple regression of the statistic method. The cotamination is a significant factor in the insulation system. The major factor is natural contamination, and the most is the salt. The salt contamination is occured by the weather conditions. The weather contaminations are wind, precipitation, temperature, relative humidity, etc. The effects of those are different, and the correlation is showed numerically by using the multiple regression method of the statistic method. With this, the estimation of the equivalent salt deposit density(ESDD) becomes possible by the changes of the weather conditions.

• Korean Journal of Health Education and Promotion
• /
• v.32 no.2
• /
• pp.53-63
• /
• 2015

Objectives: The purpose of this study was to investigate association of depressive symptom, fatalism with selected health behaviors among people aged 50-69 with no physical limitation in Seoul. Methods: In 2012, data were collected using a household based interview survey in Seoul. One person in each selected household aged between 50 and 69 was selected and responded. Data analysis was based on 1,190 subjects who answered they do not have any physical activity limitation. Results: Multiple logistic regression analysis showed significant association among variables including perceived health, depressive symptom and fatalism scores on some health behaviors. Multiple regression analysis showed that selected health risk behaviors(current smoking, monthly alcohol consumption, no regular health exam in two years) were significantly associated with depressive symptom and fatality scores in addition to demographic variables. The final regression model's adjusted R square was about 0.235. Conclusion: Demographic variables such as gender, age and socioeconomic status were significant variables in health behaviors and these behavioral factors were associated with perceived health, depressive symptom and fatalistic views. As a conclusion, depressive symptom and fatalism should be monitored and intervened in health education practice.

• Journal of the Korean Data and Information Science Society
• /
• v.21 no.6
• /
• pp.1319-1325
• /
• 2010

Quantile regression provides a more complete statistical analysis of the stochastic relationships among random variables. Sometimes quantile functions estimated at different orders can cross each other. We propose a new non-crossing quantile regression method applying support vector median regression to restricted regression quantile, restricted support vector quantile regression. The proposed method provides a satisfying solution to estimating non-crossing quantile functions when multiple quantiles for high dimensional data are needed. We also present the model selection method that employs cross validation techniques for choosing the parameters which aect the performance of the proposed method. One real example and a simulated example are provided to show the usefulness of the proposed method.

• Journal of the Society of Naval Architects of Korea
• /
• v.31 no.3
• /
• pp.112-118
• /
• 1994

In this paper, statistical approach to prediction of A-weighted noise level in ship cabins. based on multiple linear regression analysis, is conducted. The best regression formula is composed of seven parameters of the deadweight, the type of ship, the location of engines and cabins, the type of deckhouse and the propeller skew angle. Verification work was carried out with other 210 cabins' data in 6 ships. As a result, the formula ensures the accuracy of 3 dB(A) in 77 % of cases.

• International Journal of Naval Architecture and Ocean Engineering
• /
• v.6 no.3
• /
• pp.700-714
• /
• 2014

This study aims to identify the relations between seakeeping characteristics and hull form parameters for YTU Gulet series with cruiser stern. Seakeeping analyses are carried out by means of a computer software which is based on the strip theory and statistical short term response prediction method. Multiple regression analysis is used for numerical assessment through a computer software. RMS heave-pitch motions and absolute vertical accelerations on passenger saloon for Sea State 3 at head waves are investigated for this purpose. It is well known that while ship weight and the ratios of main dimensions are the primary factors on ship motions, other hull form parameters ($C_P$, $C_{WP}$, $C_{VP}$, etc.) are the secondary factors. In this study, to have an idea of geometric properties on ship motions of gulets three different regression models are developed. The obtained outcomes provide practical predictions of seakeeping behavior of gulets with a high level of accuracy that would be useful during the concept design stage.

• Communications for Statistical Applications and Methods
• /
• v.26 no.6
• /
• pp.539-556
• /
• 2019

This paper derive a method to solve change point regression problems via a process for obtaining consequential results using properties of a difference-based intercept estimator first introduced by Park and Kim (Communications in Statistics - Theory Methods, 2019) for outlier detection in multiple linear regression models. We describe the statistical properties of the difference-based regression model in a piecewise simple linear regression model and then propose an efficient algorithm for change point detection. We illustrate the merits of our proposed method in the light of comparison with several existing methods under simulation studies and real data analysis. This methodology is quite valuable, "no matter what regression lines" and "no matter what the number of change points".

• Korea Journal of Hospital Management
• /
• v.26 no.2
• /
• pp.17-26
• /
• 2021

Purposes: This study aims to identify factors affecting dental university hospitals' profitability and understand recent their business condition. Methodology: Data from 2016 to 2019 was collected from financial statement, public open data in 8 dental university hospitals. For the study, multiple regression test with stepwise selection was applied. Findings: First of all, 9 out of 19 independent variables were selected by stepwise selection. As a result of multiple regression test with selected independent variables and the dependent variable(operating profit margin ratio), the factors affecting hospitals' profitability were the number of dental unit chair, hospital location, debt ratio, total capital turnover ratio, employment cost rate, material cost rate, management expense rate, the number of patient per a dentist. Practical Implication: To improve dental university hospitals' profitability, hospitals specifically analysis and manage their cost such as employment, material and management cost and seek effectiveness by managing the proper number of patient per a dentist.

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