Brownian Motion: Theory and Applications

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Covers continuous random variables, probability density functions, and distributions, with practical examples.

Introduces probability theory, random variables, and distributions, with a focus on their applications in atomic diffusion.

Explores random variables, expectation, and independence in probability theory.

Covers the review of random variables, probability density functions, variance, and Gaussian processes.

Covers advanced probability concepts, including random variables and expected value calculation.

Covers conditional density, independence of random variables, expectation, and variance calculation.

Explores continuous random variables, density functions, and distribution laws with practical examples.

Explores conditional density, expectations, and independence of random variables with practical examples.

Explains the Law of Large Numbers and its application to random variables.