Data Compression and Statistical Estimation

This chapter explores the intersection of statistical distributions, data compression techniques, and machine learning methods for efficiently representing high-dimensional data. Key concepts such as Kolmogorov complexity, sample mean, and PCA are discussed within the framework of statistical estimation, highlighting their implications in both theory and practice.