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Professor Dr. Mohammed Abdul-Hussein Mohammed, Assistant Dean for Administrative and Financial Affairs at Al-Qadisiyah Polytechnic College, participated as a member of the defense committee for a Master’s thesis at the College of Administration and Economics, University of Al-Qadisiyah.

The defense took place in the Department of Statistics for the student Tuqa Hashim, regarding her thesis titled: “Using Regularization Methods in Principal Component Analysis with Practical Application.”

The thesis aimed to address challenges in multidimensional data analysis characterized by a large number of variables and high correlations, which often lead to difficulties in interpreting results and reduced efficiency of statistical models. The study focused on integrating Principal Component Analysis (PCA) with variable selection methods, such as LASSO and Elastic Net, to construct a more stable and interpretable statistical model.

Furthermore, the research involved developing hybrid models that simultaneously combine dimension reduction techniques and variable selection. This approach aims to improve estimation accuracy and enhance the predictive power of statistical models, particularly in the case of high-dimensional data or when significant correlations exist between variables.

Through simulation and practical application, the results demonstrated that the proposed models—combining PCA with regularization methods—outperform traditional models. These methods contributed to improving the stability of statistical estimates and mitigating multicollinearity issues, while also increasing the model’s explanatory power. This enhances the potential for employing such techniques in analyzing complex data and building more precise statistical models suitable for various applications.

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