A hierarchical, searchable Knowledge Base Module (KBM) that converts Probability Theory into a practical, step‑by‑step digital reference — from foundational definitions to applied probabilistic models and reproducible examples for students, researchers, and professionals.

A structured, searchable knowledge base for mastering regression analysis — from linear models to advanced nonlinear modeling and changing-relationships prediction — designed for students, researchers, and professionals who need fast, reliable access to organized statistical knowledge and practical implementations.