Estimation and Method of Moments

Discusses estimation methods in probability and statistics, focusing on maximum likelihood estimation and confidence intervals.

Explores statistical models, parameter estimation, and sampling distributions in probability and statistics.

Covers the fundamental concepts of statistics and their application in data science.

Explains confidence intervals, parameter estimation methods, and the central limit theorem in statistical inference.

Explores the Method of Moments, Bias-Variance tradeoff, Consistency, Plug-In Principle, and Likelihood Principle in point estimation.