ترجع صعوبة دراسة طرائق تحليل الانحدار المتعدد إلى فهم و تفسير العلاقات المتشابكة
بين المتغيرات التي تؤثر في الظاهرة المدروسة والى ضخامة البيانات التي يجب تحليلها
و بخاصة وجود بعض من هذه البيانات الشاذة .
لقد قمنا في هذا البحث بدراسة و معالجة البيانات الشاذة الموجودة في بيانات نموذج
الانحدار الخطي المتعدد في حالة وجود اثنين أو أكثر من معاملات هذا النموذج غير
معنوية ، و أوجدنا خوارزمية لحل مشكلتي وجود البيانات الشاذة من جهة و حل مشكلة
معنوية نموذج الانحدار و عدم معنوية معامل أو أكثر من جهة أخرى .
he problem with study of the ways of multiple regression analysis is related to
e to the understanding and the explanation of the complicated relations among
variables which affect the studied phenomenon and the huge amount of the
used data in particular some of this outliers.
In this research we have studied and treated the outliers in case of having two
or more non-significant parameter and we have made anew algorithm to solve
the phenomenon outliers on the one hand and solving the problem of the
significant of multiple regression.
References used
Johnson Richard A. and Wichern , Dean w.Applied multivariate statistical Analysis , 6th ed . , pearson prentice Hall ,2007
NETREK J ., WASSERMAN W ., 1992 – M.KUTNER – Applied linear statistical models experimental designer by richarel .Irwin,P 255
In this research ,we studied the problem of multicollinearity among
independent variables in the multiple regression model this matter
leads to a mistake in one of the essential conditions of the multiple
regression model and getting incorrect res
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