Random Walk and Diffusion

Related lectures (30)

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Delves into probability, statistics, paradoxes, and random variables, showcasing their real-world applications and properties.

Covers the theory of Brownian motion, diffusion, and random walks, with a focus on Einstein's theory for one-dimensional motion.

Explores the estimation of expectation for discrete random variables, emphasizing its importance in probability theory.

Covers the basics of probability distributions, including mean, variance, and properties of random variables.

Covers Simpson's paradox, probability distributions, and real-life examples in probability and statistics.

Covers p-quantile, normal approximation, joint distributions, and exponential families in probability and statistics.

Covers Markov's and Chebyshev's Inequalities for random variables and probability distributions.

Explores modes of convergence in probability and statistics, illustrating concepts with examples and discussing the continuity theorem.

Discusses properties and functions of discrete random variables, including binomial and negative binomial distributions.

Provides an overview of Generalized Linear Models, focusing on logistic and Poisson regression models, and their implementation in R.