Statistical physics, one of the fundamental theories of physics, uses methods of statistics in solving physical problems. It can describe a wide variety of fields with an inherently stochastic nature. Examples include problems such as nuclear reactions, and topics in the fields of biology, chemistry, neurology and even some social sciences such as sociology.

The term statistical physics encompasses statistical approaches to classical mechanics and quantum mechanics. Statistical mechanics is then often used as a synonym. When the context requires a distinction, one uses the terms classical statistical mechanics and quantum statistical mechanics.

A statistical approach can work well in classical systems when the number of degrees of freedom (and so the number of variables) is so large that exact solution is not possible, or not really useful. Statistical mechanics can also describe work in non-linear dynamics, chaos theory, thermal physics, fluid dynamics (particularly at low Knudsen numbers), or plasma physics.

Although some problems in statistical physics can be solved analytically using approximations and expansions, most current research utilizes the large processing power of modern computers to simulate or approximate solutions. A common approach to statistical problems is to use a Monte Carlo simulation, to yield insight into the dynamics of a complex system.