Equation modeling of Sembulan River , Sabah , as a case study using backward stepwise multiple linear regression

An equation modeling on Sembulan river, Sabah, Malaysia, has been undertaken using a backward stepwise multiple linear regression. A good performance has been obtained using a log transformation on water quality data designated as predictors and dependent variable. The regression model is in accord...

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Main Authors:	Rita Sundari, Musa Ahmad, Lee , Yook Heng
Format:	Article
Published:	Universiti Kebangsaan Malaysia 2006
Online Access:	http://journalarticle.ukm.my/3982/ http://journalarticle.ukm.my/3982/

id	ukm-3982
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spelling	ukm-39822012-03-28T03:13:56Z http://journalarticle.ukm.my/3982/ Equation modeling of Sembulan River , Sabah , as a case study using backward stepwise multiple linear regression Rita Sundari, Musa Ahmad, Lee , Yook Heng An equation modeling on Sembulan river, Sabah, Malaysia, has been undertaken using a backward stepwise multiple linear regression. A good performance has been obtained using a log transformation on water quality data designated as predictors and dependent variable. The regression model is in accordance with the ANOVA result. The temperature, biochemical oxygen demand (BOD), Echerichia Coli, Pb and nitrate were described as continuous predictors, while the river location (downstream, municipal and upstream) was designated as independent string grouping variable, and the chemical oxygen demand (COD) was set up as the dependent variable. The string grouping variable was converted to its dummy variable, which in turn led to design of a three-equation model with respect to river location. The results show that BOD has a strong effect on COD, while Pb and nitrate show less effect on COD. The temperature gives little negative effect on COD, while other variables such as pH, salinity and Cd are excluded from the river modeling since they induce insignificant effects based on backward criterion probability of F-value ≥ 0.100. Using the general linear model with LSD mode, it is revealed that predictor(s) show a remarkable discriminant effect between upstream and municipal/downstream on the 0.05 level. The most effect came from salinity indicated by the canonical discriminant function based on Wilks’ lambda. Universiti Kebangsaan Malaysia 2006-12 Article PeerReviewed Rita Sundari, and Musa Ahmad, and Lee , Yook Heng (2006) Equation modeling of Sembulan River , Sabah , as a case study using backward stepwise multiple linear regression. Sains Malaysiana, 35 (2). pp. 1-7. ISSN 0126-6039 http://www.ukm.my/jsm/english_journals/vol35num2_2006/vol35num2_06page1-7.html
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Kebangasaan Malaysia
building	UKM Institutional Repository
collection	Online Access
description	An equation modeling on Sembulan river, Sabah, Malaysia, has been undertaken using a backward stepwise multiple linear regression. A good performance has been obtained using a log transformation on water quality data designated as predictors and dependent variable. The regression model is in accordance with the ANOVA result. The temperature, biochemical oxygen demand (BOD), Echerichia Coli, Pb and nitrate were described as continuous predictors, while the river location (downstream, municipal and upstream) was designated as independent string grouping variable, and the chemical oxygen demand (COD) was set up as the dependent variable. The string grouping variable was converted to its dummy variable, which in turn led to design of a three-equation model with respect to river location. The results show that BOD has a strong effect on COD, while Pb and nitrate show less effect on COD. The temperature gives little negative effect on COD, while other variables such as pH, salinity and Cd are excluded from the river modeling since they induce insignificant effects based on backward criterion probability of F-value ≥ 0.100. Using the general linear model with LSD mode, it is revealed that predictor(s) show a remarkable discriminant effect between upstream and municipal/downstream on the 0.05 level. The most effect came from salinity indicated by the canonical discriminant function based on Wilks’ lambda.
format	Article
author	Rita Sundari, Musa Ahmad, Lee , Yook Heng
spellingShingle	Rita Sundari, Musa Ahmad, Lee , Yook Heng Equation modeling of Sembulan River , Sabah , as a case study using backward stepwise multiple linear regression
author_facet	Rita Sundari, Musa Ahmad, Lee , Yook Heng
author_sort	Rita Sundari,
title	Equation modeling of Sembulan River , Sabah , as a case study using backward stepwise multiple linear regression
title_short	Equation modeling of Sembulan River , Sabah , as a case study using backward stepwise multiple linear regression
title_full	Equation modeling of Sembulan River , Sabah , as a case study using backward stepwise multiple linear regression
title_fullStr	Equation modeling of Sembulan River , Sabah , as a case study using backward stepwise multiple linear regression
title_full_unstemmed	Equation modeling of Sembulan River , Sabah , as a case study using backward stepwise multiple linear regression
title_sort	equation modeling of sembulan river , sabah , as a case study using backward stepwise multiple linear regression
publisher	Universiti Kebangsaan Malaysia
publishDate	2006
url	http://journalarticle.ukm.my/3982/ http://journalarticle.ukm.my/3982/
first_indexed	2023-09-18T19:40:19Z
last_indexed	2023-09-18T19:40:19Z
_version_	1777405546012344320

Equation modeling of Sembulan River , Sabah , as a case study using backward stepwise multiple linear regression

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