Groups
Category
Level
Conditional probability measures the chance of event A happening when we already know event B happened.
Kolmogorov’s axioms define probability as a measure on events: non-negativity, normalization, and countable additivity.
Probability theory formalizes uncertainty using a sample space, events, and a probability measure that obeys clear axioms.
Variance measures how spread out a random variable is around its mean, while covariance measures how two variables move together.
Probability quantifies uncertainty by assigning numbers between 0 and 1 to events in a sample space.