Estimation theory is a branch of statistics that focuses on estimating the parameters of a statistical model based on observed data. It provides methods to make inferences about population characteristics, such as means or variances, using sample data. Common techniques include point estimation and interval estimation, which help quantify uncertainty in the estimates. In estimation theory, various approaches like maximum likelihood estimation and Bayesian estimation are used to derive estimates. These methods help researchers and analysts make informed decisions in fields such as engineering, economics, and social sciences, where accurate parameter estimation is crucial for effective modeling and prediction.