Sampling encompasses a range of interrelated concepts across different fields, each applying it uniquely to solve specific problems. Despite these variations, they share a common underlying principle: the extraction of representative, discrete subsets (samples) from larger, sometimes continuous, entities.
- In signal processing, sampling is the reduction of a continuous signal to a discrete signal.
- In statistics, sampling is the selection of a subset of individuals from within a population to estimate characteristics of the whole population.
- pseudo-random number sampling, which generate pseudo-random numbers from a probability distribution
The core idea of sampling is interconnected across disciplines. For example, in Monte Carlo simulation, the concept of random sampling can be interpreted as both a signal processing technique and a statistical method.