Exploring Statistical Efficiency and Estimation

This chapter examines the concept of efficiency in statistics, contrasting broader definitions of statistics with Fisher's narrower view. It discusses the significance of estimating parameters from data, the relationship between statistical methods and machine learning, and various types of convergences in estimation. The chapter emphasizes the importance of consistency and minimizing variance in estimators, while connecting foundational statistical concepts to modern applications in artificial intelligence.