In practice one constructs an estimator as a function of an available sample of size "n", and then imagines being able to keep collecting data and expanding the sample "ad infinitum". In this way one would obtain a sequence of estimates indexed by "n", and consistency is a property of what occurs as the sample size “grows to infinity”. If the sequence of estimates can be mathematically shown to converge in probability to the true value "θ"0, it is called a consistent estimator; otherwise the estimator is said to be inconsistent.