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The Mathematical Model of Robust Regression for
Body Mass Index (BMI) Using MM Estimation
Siti Adawiah Binti Md Yusop
Supervisor: Pn. Nor Azlida Binti Aleng @ Mohamad
Bachelor of Science (Financial Mathematics)
School of Informatics and Applied Mathematics
In medical statistics research, there are many methodologies used to investigate and to
model the relationship between two or more variables. The existence of an outliers makes
a model fails to fit the data. The use of least squares method would not be appropriate
in solving problem containing outliers. Robust regression is the most popular method that
has been used to detect outliers and to provide resistant results in the presence of outliers
in the data set. In this study, MM estimation is used to develop a best fit regression model
using Statistical Analysis System (SAS). The purpose of this study is to detect outliers in
Body Mass Index (BMI) data. This approach is extremely useful in identifying outliers and
assessing the adequacy of a fitted model.
885 | UMT UNDERGRADUATE RESEARCH DAY 2018