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The Mathematical Model of Robust Regression
for Tuberculosis Using MM-Estimator
Nurhafizah Binti Othman
Supervisor: Madam Nor Azlida Binti Aleng@Mohamad
Bachelor of Science (Financial Mathematics)
School of Informatics and Applied Mathematics
Outliers detection is one important method in statistics research as it is able to help the
process of constructing the best-fit model. One of the famous methods in outliers
detection is robust regression. This method can be used to provide resistant outcomes in
the data set containing outliers. The purpose of this study is to identify the presence of
outliers using MM-estimator and build the best-fit model by using the medical data. The
tuberculosis data is used due to the fact that this fatal infectious bacterial diseases still
spreading in Malaysia and worldwide. In this paper, the contributing factors of
tuberculosis are gender, hypertensive diseases, smoking status, low body weight and
diabetes diseases. By using this five variables, the fitted model of tuberculosis can be
develop using Statistics Analysis System (SAS) software.
869 | UMT UNDERGRADUATE RESEARCH DAY 2018