Free SOA Exam P (Probability) Lessons
All 31 SOA Exam P (Probability) lessons are free to read, each with worked examples. Just a free account, no card.
General Probability
- Set Functions, Sample Spaces, and Axioms of Probability (25 min)
- Combinations and Permutations (17 min)
- Independence and Probabilities of Independent Events (27 min)
- Mutually Exclusive Events (14 min)
- Addition and Multiplication Rules (14 min)
- Conditional Probability (23 min)
- Bayes' Theorem and Law of Total Probability (23 min)
- Permutations, Ordered Counting, and the Multiplication Principle (20 min)
- Bayesian Odds, Likelihood Ratios, and Base-Rate Traps (16 min)
Univariate Random Variables
- Probability, Random Variables, PDFs, and CDFs (16 min)
- Conditional Probabilities for Random Variables (15 min)
- Expected Values: Moments, Mode, Median, and Percentiles (21 min)
- Variance, Standard Deviation, and Coefficient of Variation (17 min)
- Insurance Payments: Deductibles, Coinsurance, Benefit Limits, and Inflation (26 min)
- Moments of Loss and Payment Random Variables (23 min)
- Moment Generating Functions (12 min)
- Common Parametric Distributions (15 min)
- Discrete Counting Distributions: Binomial, Negative Binomial, Hypergeometric (14 min)
- Waiting-Time Distributions: Geometric and Poisson (11 min)
- Discrete Uniform Random Variables (10 min)
- The Gamma Distribution and the Poisson Connection (11 min)
- The Beta Distribution (11 min)
Multivariate Random Variables
- Joint Probability Functions and Joint CDFs for Discrete Random Variables (20 min)
- Conditional and Marginal Probability Functions for Discrete Random Variables (18 min)
- Moments for Joint, Conditional, and Marginal Discrete Distributions (23 min)
- Variance and Standard Deviation for Conditional and Marginal Distributions (18 min)
- Covariance and Correlation Coefficient for Discrete Random Variables (15 min)
- Joint Distribution of Order Statistics (19 min)
- Linear Combinations of Independent Discrete and Normal Random Variables (16 min)
- Moments for Linear Combinations of Independent Random Variables (20 min)
- Central Limit Theorem: Approximations for Linear Combinations of iid Random Variables (22 min)