Statistical consistency refers to the property of an estimator in statistics, where the estimator converges to the true value of a parameter as the sample size increases. In simpler terms, as you collect more data, the estimates you make become more accurate and reliable. This concept is crucial in ensuring that statistical methods yield valid results over time. For example, if you are estimating the average height of a group of people using a sample, a consistent estimator will provide results that get closer to the actual average height of the entire group as you include more individuals in your sample. This reliability is essential in fields like economics, medicine, and social sciences.