Large sample theory

Large sample theory refers to statistical methods that apply to datasets with a significant number of observations. It suggests that as the size of a sample increases, the estimates of population parameters (like averages) become more accurate and follow certain mathematical properties, such as normal distribution. This theory underpins many statistical analyses, ensuring that conclusions drawn from large samples are reliable. It helps in making predictions and informed decisions in various fields, including economics, healthcare, and social sciences, by providing a solid foundation for interpreting data with confidence.