stohastinen

Stohastinen is the Finnish term used to describe phenomena, models or processes that involve randomness and probabilistic uncertainty. The term derives from the Greek stochastikos, meaning able to guess or conjecture, and entered mathematical usage to distinguish random, probability-based models from deterministic ones.

In mathematics and statistics, a stochastic process is a family {X_t} of random variables indexed by time t, which can be discrete or continuous. Each realization yields a possible evolution of a system, while the probabilistic structure specifies distributions, expectations and other characteristics. Stochastic models are often contrasted with deterministic ones, where a single outcome is fixed by initial conditions.

Its analysis uses probability theory, stochastic calculus for continuous-time models, and techniques such as Monte Carlo simulation. Important classes include Markov processes (memoryless processes), Poisson processes (random events in time), Brownian motion (continuous random movement) and Gaussian processes.

Applications span finance (stock price modeling, option pricing), physics (diffusion and particle transport), engineering, biology, and computer science (randomized algorithms and probabilistic graphical models). In Finnish usage, stohastinen serves as the general descriptor for these methods and phenomena.