Lectures related to Birth Month Impact on Athlete Success

Explores denoising signals with Gaussian mixture models and EM algorithm, EMG signal analysis, and image segmentation using Markovian models.

Explores continuous random variables and their properties, including support and cumulative distribution functions.

Introduces linear regression, generalized linear models, and mixed-effect models for regression analysis.

Explores the assumptions and checking methods for Gaussian linear regression models using residuals and graphical plots.

Introduces multivariate statistics, covering normal distribution properties and characteristic functions.

Covers probability distributions, moments, and continuous random variables.

Explores linear regression estimation, hypothesis testing, and practical applications in statistics.

Explores joint random variables, conditional density, and independence in probability and statistics.