Lectures related to Diffusion of Neutrons

Explores continuous random variables, density functions, joint variables, independence, and conditional densities.

Explains the two-group method, group structures, and multi-group constants.

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

Explores the diffusion equation, flux, diffusivity, Fick's Law, boundary conditions, and concentration-dependent diffusion coefficient.

Introduces key concepts in probability and statistics, covering random experiments, events, intersections, unions, and more.

Explores conditional probability, Bayes' theorem, and prediction decomposition for informed decision-making.

Explores variance, covariance, and practical applications in statistics and probability.

Explores the Central Limit Theorem, covariance, correlation, joint random variables, quantiles, and the law of large numbers.