Learn probability theory through hands-on Python examples and interactive visualizations. This comprehensive guide covers fundamental concepts from basic probability rules to advanced topics like Bayes’ theorem and probability distributions.
Topics Covered¶
Fundamental probability concepts and axioms
Conditional probability and independence
Bayes’ theorem and applications
Random variables and distributions
Expected value and variance
Common probability distributions (Binomial, Poisson, Normal, etc.)
Interactive Python examples and visualizations
Access the Full Guide¶
The complete probability guide is available as an interactive Jupyter Book with hands-on examples you can explore and modify.