Probability Theory models and quantifies uncertainty in events:
- 🧮 Bernoulli and Binomial Distributions measure the probability of k successes in n independent trials.
- 🔄 Uniform Distributions assign equal probability to each outcome in a finite sample space.
- 🎲 Random Variables map experiment outcomes to numerical values for analysis.
- ☁️ Conditional Probability measures the probability of an event given that another event has occurred.
- 🎯 Bayes’ Theorem updates the probability of a hypothesis based on new evidence.