Mixture models: taste heterogeneity

Explores mixture models, including discrete and continuous mixtures, and their application in capturing taste heterogeneity in populations.

Explores bias, variance, and confidence intervals in parameter estimation using examples and distributions.

Discusses estimation methods in probability and statistics, focusing on maximum likelihood estimation and confidence intervals.

Explores probability distributions for random variables in air pollution and climate change studies, covering descriptive and inferential statistics.

Covers continuous random variables, probability density functions, and distributions, with practical examples.