Investigating something scientifically usually means trying to make predictions about what is going to happen. But as good as the scientific models are, they only very rarely make perfect predictions. Instead, scientists usually make predictions that are probabilistic in nature. Making valid probabilistic models is important to the inductive reasoning at the heart of scientific thinking about the world.

But the problem with probability - and induction in general, or logical thinking of any kind - is that it requires certain assumptions. In a new article, I discuss the Application of Probability in Physics and what assumptions are applied in different probability approaches, from classical probability theory to Bayesian statistics to the frequentism approach which is usually applied in physics.

Of course, things in probability really get interesting when it comes to the realm of quantum physics. The way probability manifests in quantum physics warrants its own detailed discussion ... but the best starting place is in understanding the less esoteric aspects of probability.

## Comments

BORING!!!!!!!!

Numbers are the Supreme Court of science. However Godel proved that we may not prove everything. Physics needs numbers. There must be Physics Foibles!!

very interesting. thanks

informative

i wonder why someone would call this boring. Good thinking.

probability in physics: i never thought about it…haha

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Probability is a mathematical branch. In mathematics probability is calculated with consistency with a set of axioms. In physics we have uncertainty defined by the entropy that is bounded by a physical law (the second law). Namely, entropy tends to increase to its maximum.

For example, the average of many polls in which one picks, randomly, 1 out of 3 choices, will yeild a distribution of 50%:29%:21% and not 33%:33%:33% as is expected from simple probability calculations. Laws of nature (the second law) can tell us something about the probabilities of probabilities. The function that describes the most probable distribution of the various events is called the distribution function.

See: http://www.entropy-book.com