Chapter Overview
This chapter covers the fundamental concepts of probability that form the foundation for everything else in Exam P. You'll learn about sample spaces, events, probability rules, and how to calculate probabilities using various techniques.
5
Sections
15+
Simulations
20+
Practice Problems
~15%
Of Exam P
Sections
1.1 Properties of Probability
Sample spaces, events, probability axioms, and fundamental rules
Sample Space & EventsProbability AxiomsComplement RuleAddition RuleVenn Diagrams
1.2 Methods of Enumeration
Counting techniques: permutations, combinations, multiplication principle
Multiplication PrinciplePermutationsCombinationsBinomial Coefficients
1.3 Conditional Probability
Probability given prior information, multiplication rule
Conditional Probability DefinitionMultiplication RuleTree Diagrams
1.4 Independent Events
Events that do not affect each other's probabilities
Independence DefinitionTesting IndependenceMultiple Independent Events
1.5 Bayes' Theorem
Updating probabilities with new information
Law of Total ProbabilityBayes' FormulaPrior vs Posterior Probabilities
Key Formulas You'll Learn
Complement Rule
P(A) = 1 - P(A')
Addition Rule
P(A∪B) = P(A) + P(B) - P(A∩B)
Conditional Probability
P(A|B) = P(A∩B) / P(B)
Bayes' Theorem
P(B|A) = P(A|B)·P(B) / P(A)