Families of Distributions: PDFs and CDFs

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

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

Explores quantiles, sampling, and histogram density for understanding distributions and constructing confidence intervals.

Discusses probability distributions and the Central Limit Theorem, emphasizing their importance in data science and statistical analysis.

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