In statistical inference, a numerical value summarizes a characteristic of a population. This value, often unknown, represents a true population attribute like the mean or proportion. Understanding this concept is fundamental to making informed conclusions about the entire group based on sample data. For example, the average height of all adult women in a country is a population characteristic, and estimating this average is a common statistical goal.
Accurate determination or estimation of these population characteristics is crucial for informed decision-making across various fields, from public health to business analytics. Historically, the development of statistical methods has heavily focused on strategies to reliably estimate these values despite the impracticality of directly measuring the entire population. The ability to infer these true population values from smaller, manageable samples is the cornerstone of inferential statistics.
