Domebytes

📘 Day 0 — Probability Basics + PMF & PDF Start: Nov 16 — Mode A (zero-knowledge). Use this page to learn & post on your blog. What you'll learn today Probability = the chance of an event happening. Values always lie between 0 and 1 . Random Variable (RV) — a number we give to an outcome. Example: coin → Heads = 1, Tails = 0; dice → result 1..6. PMF — Probability Mass Function (very simple) Used for discrete variables (dice, coin, counts). PMF lists P(X = x) for each possible x. Example (fair die): P(X=1)=1/6, P(X=2)=1/6, …, P(X=6)=1/6. Sum of all PMF values = 1. PDF — Probability Density Function (very simple) Used for continuous variables (time, height). PDF is not a probability at a point — instead probability is area under curve. Example: f(x)=1 for 0<x<1 → P(0.2<X<0.7)=area=0.5. Total area under PDF = 1. Quick summary PMF → discrete, probabilities add up PDF → continuous, area under curve = 1 Random variable = number representing outcome 📝 Your Notes (saved locally) S…