Free SOA Exam P (Probability) Lessons
All 31 SOA Exam P (Probability) lessons are free to read, each with worked examples and audio narration. No signup required.
General Probability
- Set Functions, Sample Spaces, and Axioms of Probability (24 min)
- Combinations and Permutations (15 min)
- Independence and Probabilities of Independent Events (25 min)
- Mutually Exclusive Events (12 min)
- Addition and Multiplication Rules (12 min)
- Conditional Probability (21 min)
- Bayes' Theorem and Law of Total Probability (21 min)
- Permutations, Ordered Counting, and the Multiplication Principle (18 min)
- Bayesian Odds, Likelihood Ratios, and Base-Rate Traps (15 min)
Univariate Random Variables
- Probability, Random Variables, PDFs, and CDFs (14 min)
- Conditional Probabilities for Random Variables (12 min)
- Expected Values: Moments, Mode, Median, and Percentiles (19 min)
- Variance, Standard Deviation, and Coefficient of Variation (15 min)
- Insurance Payments: Deductibles, Coinsurance, Benefit Limits, and Inflation (24 min)
- Moments of Loss and Payment Random Variables (20 min)
- Moment Generating Functions (11 min)
- Common Parametric Distributions (14 min)
- Discrete Counting Distributions: Binomial, Negative Binomial, Hypergeometric (12 min)
- Waiting-Time Distributions: Geometric and Poisson (9 min)
- Discrete Uniform Random Variables (8 min)
- The Gamma Distribution and the Poisson Connection (9 min)
- The Beta Distribution (9 min)
Multivariate Random Variables
- Joint Probability Functions and Joint CDFs for Discrete Random Variables (18 min)
- Conditional and Marginal Probability Functions for Discrete Random Variables (17 min)
- Moments for Joint, Conditional, and Marginal Discrete Distributions (20 min)
- Variance and Standard Deviation for Conditional and Marginal Distributions (15 min)
- Covariance and Correlation Coefficient for Discrete Random Variables (14 min)
- Joint Distribution of Order Statistics (17 min)
- Linear Combinations of Independent Discrete and Normal Random Variables (14 min)
- Moments for Linear Combinations of Independent Random Variables (17 min)
- Central Limit Theorem: Approximations for Linear Combinations of iid Random Variables (20 min)