Detection of outliers in the linear regression model with application to well water pollution data on the outskirts of the city of Mosul
Abstract
The research idea is concerned with identifying the effect of outliers on the parameters of the multiple linear regression analysis models. Where the outliers values present in the data are detected and diagnosed if they are in the independent or the dependent variable, which causes an impact on the estimation of the parameters of the studied model.The extreme data types and methods of processing them have been identified to obtain a better model with high efficiency or reduce the impact of These values on the model; the MSE standard was developed to compare treatment methods and was applied to real data taken from the Dams and Water Resources Research Center, University of Mosul. As suggested by (2009) is the best in detection among the methods that have been used.
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