Lecture 1 - The Language of Risk
Lecture 2 - The Art of Counting Combinatorics
Lecture 3 - Updating Beliefs Conditional Probability
Lecture 4 - Bayes' Theorem The Update Tool
Lecture 5 - Independence The Free Pass
Lecture 6 - From Events to Numbers (Discrete RVs and PMF)
Lecture 7 - The Continuous World (Continuous RVs and PDF)
Lecture 8 - The 'Grand Unifier' (Cumulative Distribution Function)
Lecture 9 - The 'Center of Gravity' (Expected Value)
Lecture 10 - Functions of an RV (The Actuarial Toolkit)
Lecture 11 - The 'Yes/No' World (Bernoulli and Binomial)
Lecture 12 - The 'Claim Count' Model (Poisson)
Lecture 13 - The 'Waiting Time' Model (Exponential)
Lecture 14 - The 'Flexible' Model (Gamma)
Lecture 15 - The 'Everywhere' Model (Normal Distribution)
Lecture 16 - Joint Distributions (Discrete PMF)
Lecture 17 - Joint Distributions (Continuous PDF)
Lecture 18 - Independence and Conditional Distributions
Lecture 19 - Covariance (Measuring Linear Relationship)
Lecture 20 - Correlation and Variance of Sums
Lecture 21 - The '1D' Transformation (The CDF Method)
Lecture 22 - The '1D' Shortcut (Change of Variable)
Lecture 23 - The '2D' Transformation (The Jacobian Method)
Lecture 24 - The 'Aggregate Loss' Transformation (Convolution)
Lecture 25 - The 'Extreme Loss' (Order Statistics)
Lecture 26 - Conditional Expectation
Lecture 27 - The 'Tower Property' (Law of Total Expectation)
Lecture 28 - The Law of Total Variance (Eve's Law)
Lecture 29 - Conditioning Drills (Mixed Distributions)
Lecture 30 - Review (Compound vs Mixed Models)
Lecture 31 - The 'Magic Tool' (Moment-Generating Function)
Lecture 32 - The MGF 'Lookup Table'
Lecture 33 - The 'Payoff' (MGF of Independent Sums)
Lecture 34 - Advanced Tools (CGFs and Compound Sum MGF)
Lecture 35 - Week 7 Review and Capstone Drill)
Lecture 36 - The Problem of 'Tails' (Why We Need Bounds)
Lecture 37 - The 'Better' Bound (Chebyshev's Inequality)
Lecture 38 - The Law of Large Numbers (LLN)
Lecture 39 - Other Inequalities (One-Sided Chebyshev and Jensen's)
Lecture 40 - Week 8 Review and Drills
Lecture 41 - The Central Limit Theorem (CLT)
Lecture 42 - CLT Drills (Aggregate Loss Problems)
Lecture 43 - The Continuity Correction
Lecture 44 - Capstone Drill (CLT for Aggregate Losses)
Lecture 45 - The Approximation ``Decision Tree'
Lecture 46 - The 'Language' of Insurance Models
Lecture 47 - Policy Feature 1 (Deductibles)
Lecture 48 - Policy Feature 2 (Policy Limits)
Lecture 49 - Capstone (Pricing a 'Policy Layer')
Lecture 50 - Review and Introduction to Stop-Loss
Lecture 51 - The 'Master Formula' for Expected Aggregate Loss
Lecture 52 - The 'Master Algorithm' for Var(S)
Lecture 53 - Finding Severity Moments E[Y^2] and Var(Y)
Lecture 54 - The 'Master Algorithm' Drill
Lecture 55 - Week 11 Review and Capstone Drills
Lecture 56 - 'The Big Picture' Review - Part 1: The Toolkit
Lecture 57 - 'The Big Picture' Review - Part 2: The Models
Lecture 58 - Mock Exam Review - Part 1: (Q1-10)
Lecture 59 - Mock Exam Review - Part 2: (Q11-20)
Lecture 60 - Mock Exam Review - Part 3: (Q21-30)
