Lectures related to Conditional Probability Distributions

Explores Bayesian techniques for extreme value problems, focusing on MCMC analysis and the importance of proper prior information.

Covers creation and annihilation operators in quantum mechanics and their applications in harmonic oscillators.

Explores fundamental solutions, Green's formula, distributions, and convergence in Laplace equation.

Covers point estimation, confidence intervals, and hypothesis testing for smooth functions using mixed models and spline smoothing.

Explains the statistical analysis of Genome-wide Association Studies and the importance of adjusting for multiple testing.

Explores modeling neurobiological signals, focusing on spikes, firing rate, multiple state neurons, and parameter estimation.