Wang, JC2024-04-262024-04-2620242024-042024-04-26April 2024https://hdl.handle.net/10388/15647In statistics, p dimensional data are collected n times. Traditionally, the dimension of p would be larger than n; however, as technology progresses, we enter the era of big data where n is no longer much larger than p. The large ratio of p n causes pitfalls in methods and algorithms that were developed with the opposite in mind. To solve this problem, methods using random matrix theory were brought up in [4], this thesis will be focusing on results concerning the Marchenko-Pastur Law. This thesis is not a cutting-edge research, but an organized presentation of the Marchenko- Pastur Law. This is written so students and researchers can quickly grasp the ideas and methods without difficulty.application/pdfenMarchenko-Pastur LawThesis2024-04-26