Large Deviations: Theory and Applications

Related lectures (31)

Page 3 of 4

Explores convergence in probability, concentration inequalities, laws of large numbers, and properties of distributions.

Explores continuous random variables, cdf, pdf, convolution, and sum of dice.

Explores spherical symmetry in statistical mechanics and its role in phase transitions.

Covers exercises on Bayes' Theorem, moment generating functions, photon counts, disease probabilities, and distribution properties.

Covers random variables, expectation, and distributions in probability spaces.

Explores Gaussian distributions, moments, and variance calculations in probability theory.

Explores the strong convergence of random variables and the normal distribution approximation in probability and statistics.

Explores independent and identically distributed random variables, convergence, and distribution properties.

Introduces the basics of probability models, covering random variables, distributions, and statistical estimation.

Explores memorylessness in distributions, stationary processes, and estimation using MLE.