Simulations in statistics refer to the process of using a computer or other tools to mimic real-life situations and generate data in order to study and analyze statistical phenomena. Simulations allow statisticians to model random events, test hypotheses, and make predictions.
Related terms
Randomness: Randomness refers to the unpredictable nature of events or outcomes that cannot be determined with certainty beforehand.
Monte Carlo Simulation: A Monte Carlo simulation is a type of simulation that uses random sampling techniques and randomness to model complex systems or processes.
Sampling Distribution: A sampling distribution is the probability distribution of a statistic obtained from repeated random samples taken from a specific population.