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Exam STAM
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C vs STAM
Wed, 25 Apr 2018
Welcome to the TIA course for SOA Exam STAM. Many people have been wondering how Exam C compares to the new SOA exam STAM. They have about a 70% overlap, with the biggest changes between C and STAM being that Empirical Estimators (section C of the old C seminar) and simulation (section F) have been … Continue reading C vs STAM
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  • Important Tables and FAQ ... lessons ... min of video
    • General Info ...
      • How to Prepare (15:41)
      • TIA Problem System (7:45)
      • TIA Discussion Forum (5:58)
      • Video Player Keyboard Shortcuts (handout)
      • You Failed, Now What? (12:00)
    • Key Course Handouts ...
      • Study Schedule Spreadsheet (handout)
      • Exam Distribution Tables (handout)
      • Exam STAM Syllabus (handout)
      • Notation and Terminology Note (handout)
      • Section A. Formula Sheet (handout)
      • Section B. Formula Sheet (handout)
      • Section C. Formula Sheet (handout)
      • Section D. Formula Sheet (handout)
      • Section E. Formula Sheet (handout)
  • STAM-A. Loss Models ... lessons ... min of video
    • A.1 Probability Review ...
      • A.1.1 Describing Distributions (sample) (24:32)
      • A.1.2 Moments (sample) (21:25)
      • A.1.3 Generating Functions (sample) (15:27)
      • A.1.4 Joint and Conditional Distributions (sample) (16:15)
      • A.1.5 Conditional Moments (sample) (24:43)
      • A.1.6 Mixtures (sample) (16:44)
      • A.1.7 Sums of Random Variables (sample) (16:25)
    • A.2 Key Continuous Distributions ...
      • A.2.1 The Exponential Distribution (sample) (18:10)
      • A.2.2 The Gamma Distribution (sample) (17:38)
      • A.2.3 The Pareto Distribution (sample) (13:33)
      • A.2.4 Normal and Lognormal Distributions (sample) (22:07)
      • A.2.5 Uniforms and Summary (sample) (10:56)
    • A.3 Severity Models ...
      • A.3.1 Scale Parameters (sample) (13:12)
      • A.3.2 Deductibles (18:34)
      • A.3.3 Limits (23:56)
      • A.3.4 Other Adjustments (18:41)
      • A.3.5 Variances (26:36)
      • A.3.6 Decomposing Losses (Optional) (15:22)
    • A.4 Misc. Continuous Topics ...
      • A.4.1 Transformations (12:10)
      • A.4.2 Spliced Distributions (13:56)
      • A.4.3 Frailty Models (16:19)
      • A.4.4 Tail Weights (22:29)
    • A.5 Frequency Models ...
      • A.5.1 Key Discrete Distributions (20:42)
      • A.5.2 Poisson-Gamma (sample) (12:46)
      • A.5.3 (a, b, 0) Definition (12:57)
      • A.5.4 (a, b, 1) Distributions (19:47)
      • A.5.5 Moments of (a, b, 1) Distributions (16:51)
    • A.6 Aggregate Models ...
      • A.6.1 Normal Approximations (22:21)
      • A.6.2 Discrete Severities (25:03)
      • A.6.3 Deductibles Per Loss (13:07)
      • A.6.4 Aggregate Deductibles (11:39)
      • A.6.5 Continuous Aggregate Distributions (12:17)
      • A.6.6 Discretization (16:26)
  • STAM-B. Risk Measures ... lessons ... min of video
    • B.1 VaR and TVaR ...
      • B.1.1 Risk Measures (16:54)
      • B.1.2 Normal and Lognormal Distributions (15:12)
      • B.1.3 Deductibles (16:00)
    • B.2 Coherence ...
      • B.2.1 Coherence (16:54)
  • STAM-C. Parametric Estimators ... lessons ... min of video
    • C.1 Maximum Likelihood Estimators ...
      • C.1.1 Maximum Likelihood Estimators (25:06)
      • C.1.2 Special Cases (20:44)
      • C.1.3 Exponentials (sample) (20:16)
      • C.1.4 Range Depends on Parameters (18:18)
      • C.1.5 Transformations (16:54)
      • C.1.6 Calculator Methods (14:03)
    • C.2 Estimating Discrete Distributions ...
      • C.2.1 MLE for (a, b, 1) Distributions (14:00)
      • C.2.2 Which (a, b, 1) Distribution? (16:36)
    • C.3 Variances of MLEs ...
      • C.3.1 Variances of MLEs (13:27)
      • C.3.2 Fisher's Information (23:34)
      • C.3.3 Fisher's Information Continued (24:11)
      • C.3.4 Delta Method (18:37)
      • C.3.5 Delta Method Continued (11:07)
    • C.4 Hypothesis Testing ...
      • C.4.1 D(x) Plots (15:35)
      • C.4.2 p-p plots (14:37)
      • C.4.3 Hypothesis Testing (11:53)
      • C.4.4 Kolmogorov-Smirnov (29:18)
      • C.4.5 Chi-Square Tests I (24:43)
      • C.4.6 Chi-Square Tests 2 (14:53)
      • C.4.7 Score Based Models (sample) (15:26)
      • C.4.8 Likelihood Ratio Test (21:51)
      • C.4.9 Non-Normal Confidence Intervals (14:01)
  • STAM-D. Credibility ... lessons ... min of video
    • D.1 Classical Credibility ...
      • D.1.1 Credibility for Frequency (16:15)
      • D.1.2 Credibility for Aggregate Distributions (17:28)
      • D.1.3 Partial Credibility (12:11)
    • D.2 Bayesian Credibility ...
      • D.2.0a Recognizing Distributions (21:11)
      • D.2.0b Calculus Tricks (16:36)
      • D.2.1 Discrete Bayesian Credibility (28:43)
      • D.2.2 Continuous Bayesian Credibility (22:00)
      • D.2.3 Poisson/Gamma (22:33)
      • D.2.4 Binomial/Beta (27:53)
      • D.2.5 Gamma and Inverse Gamma Families (23:45)
      • D.2.6 Harder Examples (20:30)
    • D.3 Buhlmann Credibility ...
      • D.3.1 Buhlmann Credibility (23:11)
      • D.3.2 Buhlmann with Discrete Distributions (16:43)
      • D.3.3 Generalizations (26:48)
      • D.3.4 Exact Credibility (18:48)
      • D.3.5 Buhlmann as Linear Approximation of Bayesian (25:47)
      • D.3.6 Normal/Normal and Lognormal/Normal (37:12)
    • D.4 Empirical Credibility ...
      • D.4.1 Non-Parametric Credibility: Uniform Case (25:12)
      • D.4.2 Non-Parametric Credibility: General Case (31:05)
      • D.4.3 Semi-Parametric Credibility: Poisson Case (18:52)
      • D.4.4 Semi-Parametric Credibility: Non-Poisson Case (12:47)
  • STAM-E. General Insurance ... lessons ... min of video
    • E.1 Reserving ...
      • E.1.1 Expected Loss Ratio Method (12:03)
      • E.1.2 Chain Ladder Method: Intro (18:04)
      • E.1.3 Chain Ladder Method: Development Factors (19:29)
      • E.1.4 Discounted Reserves (18:22)
      • E.1.5 Bornhuetter-Ferguson Method (20:03)
      • E.1.6 Incurred vs Paid Factors (14:17)
      • E.1.7 Frequency and Severity Part 1 (18:36)
      • E.1.8 Frequency and Severity Part 2 (Closure Method) (21:25)
    • E.2 Ratemaking ...
      • E.2.1 Introduction to Ratemaking (13:57)
      • E.2.2 The Parallelogram Method (27:45)
      • E.2.3 Trend Factors (26:07)
      • E.2.4 Loss Ratio Method (21:35)
      • E.2.5 Loss Cost Method (19:04)
      • E.2.6 Multiple Factors (19:39)
    • E.3 Reinsurance and Health ...
      • E.3.1 Auto and Homeowner's Insurance (19:10)
      • E.3.2 Health Insurance (18:24)
      • E.3.3 ILFs (21:36)
      • E.3.4 Reinsurance (16:18)
      • E.3.5 Individual Risk Rating (11:12)
  • A.1 Probability Review ... lessons ... min of video
    • A.1.1 Describing Distributions ...
      • A.1.1 #1 (1:43)
      • A.1.1 #2 (3:04)
      • A.1.1 #3 (1:03)
      • A.1.1 #4 (1:24)
    • A.1.2 Moments ...
      • A.1.2 #1 (7:30)
      • A.1.2 #2 (2:24)
      • A.1.2 #3 (2:33)
      • A.1.2 #4 (2:19)
      • A.1.2 #5 (3:38)
      • A.1.2 #6 (3:16)
      • A.1.2 #7 (6:03)
      • A.1.2 #8 (2:26)
      • A.1.2 #9 (1:53)
    • A.1.3 Generating Functions ...
      • A.1.3 #1 (4:35)
      • A.1.3 #2 (4:06)
      • A.1.3 #3 (3:50)
      • A.1.3 #4 (1:03)
      • A.1.3 #5 (3:20)
      • A.1.3 #6 (2:17)
    • A.1.4 Joint and Conditional Distributions ...
      • A.1.4 #1 (0:28)
      • A.1.4 #2 (1:57)
    • A.1.5 Conditional Moments ...
      • A.1.5 #1 (2:28)
      • A.1.5 #2 (2:36)
      • A.1.5 #3 (2:16)
    • A.1.6 Mixtures ...
      • A.1.6 #1 (3:19)
      • A.1.6 #2 (3:11)
      • A.1.6 #3 (2:46)
      • A.1.6 #4 (1:02)
    • A.1.7 Sums of Random Variables ...
      • A.1.7 #1 (1:59)
      • A.1.7 #2 (1:00)
      • A.1.7 #3 (4:53)
  • A.2 Key Continuous Distributions ... lessons ... min of video
    • A.2.1 The Exponential Distribution ...
      • A.2.1 #1 (2:04)
      • A.2.1 #2 (2:05)
      • A.2.1 #3 (4:25)
      • A.2.1 #4 (6:10)
      • A.2.1 #5 (3:35)
      • A.2.1 #6 (2:17)
      • A.2.1 #7 (1:07)
      • A.2.1 #8 (4:24)
    • A.2.2 The Gamma Distribution ...
      • A.2.2 #1 (2:07)
      • A.2.2 #2 (2:54)
    • A.2.3 The Pareto Distribution ...
      • A.2.3 #1 (2:12)
      • A.2.3 #2 (4:09)
      • A.2.3 #3 (2:08)
      • A.2.3 #4 (1:14)
      • A.2.3 #5 (0:59)
      • A.2.3 #6 (3:36)
    • A.2.4 Normal and Lognormal Distributions ...
      • A.2.4 #1 (3:41)
      • A.2.4 #2 (2:04)
      • A.2.4 #3 (2:19)
      • A.2.4 #4 (3:33)
      • A.2.4 #5 (1:44)
      • A.2.4 #6 (3:59)
      • A.2.4 #7 (3:15)
      • A.2.4 #8 (3:55)
      • A.2.4 #9 (3:47)
      • A.2.4 #10 (3:46)
      • A.2.4 #11 (3:02)
      • A.2.4 #12 (2:54)
      • A.2.4 #13 (1:03)
      • A.2.4 #14 (3:19)
      • A.2.4 #15 (3:20)
    • A.2.5 Uniforms and Summary ...
      • A.2.5 #2 (0:44)
      • A.2.5 #3 (2:11)
  • A.3 Severity Models ... lessons ... min of video
    • A.3.1 Scale Parameters ...
      • A.3.1 #1 (3:29)
      • A.3.1 #2 (2:21)
      • A.3.1 #3 (0:39)
      • A.3.1 #4 (2:05)
      • A.3.1 #5 (2:00)
      • A.3.1 #10 (3:28)
    • A.3.2 Deductibles ...
      • A.3.2 #1 (2:16)
      • A.3.2 #2 (1:53)
      • A.3.2 #3 (2:16)
      • A.3.2 #4 (2:38)
      • A.3.2 #5 (1:17)
      • A.3.2 #6 (1:09)
      • A.3.2 #7 (2:19)
      • A.3.2 #8 (5:36)
    • A.3.3 Limits ...
      • A.3.3 #1 (4:43)
      • A.3.3 #2 (3:57)
      • A.3.3 #3 (3:07)
      • A.3.3 #4 (3:07)
      • A.3.3 #5 (3:09)
    • A.3.4 Other Adjustments ...
      • A.3.4 #1 (1:14)
      • A.3.4 #2 (5:20)
      • A.3.4 #3 (2:09)
      • A.3.4 #4 (2:27)
      • A.3.4 #5 (3:01)
      • A.3.4 #6 (1:55)
      • A.3.4 #7 (1:40)
    • A.3.5 Variances ...
      • A.3.5 #1 (1:18)
      • A.3.5 #2 (3:13)
      • A.3.5 #3 (6:17)
      • A.3.5 #4 (6:31)
      • A.3.5 #5 (3:06)
    • A.3.6 Decomposing Losses (Optional) ...
      • A.3.6 #1 (1:39)
      • A.3.6 #2 (1:47)
      • A.3.6 #3 (3:08)
  • A.4 Misc. Continuous Topics ... lessons ... min of video
    • A.4.1 Transformations ...
      • A.4.1 #1 (4:40)
      • A.4.1 #2 (0:59)
      • A.4.1 #3 (2:04)
      • A.4.1 #4 (1:59)
      • A.4.1 #5 (1:54)
    • A.4.2 Spliced Distributions ...
      • A.4.2 #1 (1:36)
      • A.4.2 #2 (3:08)
      • A.4.2 #3 (4:53)
      • A.4.2 #4 (4:18)
      • A.4.2 #5 (7:06)
      • A.4.2 #6 (5:28)
      • A.4.2 #7 (2:15)
      • A.4.2 #8 (2:59)
    • A.4.3 Frailty Models ...
      • A.4.3 #1 (3:08)
      • A.4.3 #2 (2:29)
      • A.4.3 #3 (4:09)
      • A.4.3 #4 (2:59)
      • A.4.3 #5 (2:49)
      • A.4.3 #6 (2:55)
      • A.4.3 #7 (2:59)
    • A.4.4 Tail Weights ...
      • A.4.4 #1 (4:38)
      • A.4.4 #2 (1:06)
  • A.5 Frequency Models ... lessons ... min of video
    • A.5.1 Key Discrete Distributions ...
      • A.5.1 #3 (2:17)
      • A.5.1 #4 (4:32)
      • A.5.1 #5 (1:36)
      • A.5.1 #6 (1:43)
      • A.5.1 #7 (0:47)
      • A.5.1 #8 (1:46)
      • A.5.1 #9 (2:45)
      • A.5.1 #10 (1:20)
      • A.5.1 #11 (3:31)
      • A.5.1 #12 (1:24)
    • A.5.2 Poisson-Gamma ...
      • A.5.2 #1 (1:56)
      • A.5.2 #2 (0:57)
      • A.5.2 #3 (1:53)
      • A.5.2 #4 (2:19)
    • A.5.3 (a, b, 0) Definition ...
      • A.5.3 #1 (1:41)
      • A.5.3 #2 (2:30)
      • A.5.3 #3 (0:59)
    • A.5.4 (a, b, 1) Distributions ...
      • A.5.4 #1 (0:43)
      • A.5.4 #2 (2:21)
      • A.5.4 #3 (3:01)
    • A.5.5 Moments of (a, b, 1) Distributions ...
      • A.5.5 #1 (1:01)
      • A.5.5 #2 (3:10)
  • A.6 Aggregate Models ... lessons ... min of video
    • A.6.1 Normal Approximations ...
      • A.6.1 #3 (2:56)
      • A.6.1 #5 (2:30)
      • A.6.1 #10 (2:53)
      • A.6.1 #11 (3:16)
      • A.6.1 #12 (2:31)
      • A.6.1 #13 (4:10)
      • A.6.1 #14 (0:41)
      • A.6.1 #17 (0:51)
      • A.6.1 #18 (2:05)
      • A.6.1 #27 (4:35)
      • A.6.1 #28 (3:55)
    • A.6.2 Discrete Severities ...
      • A.6.2 #2 (5:41)
      • A.6.2 #3 (1:25)
      • A.6.2 #4 (3:14)
    • A.6.3 Deductibles Per Loss ...
      • A.6.3 #1 (1:16)
      • A.6.3 #2 (1:34)
      • A.6.3 #3 (1:14)
      • A.6.3 #4 (1:18)
    • A.6.4 Aggregate Deductibles ...
      • A.6.4 #1 (5:34)
      • A.6.4 #2 (6:56)
      • A.6.4 #3 (1:06)
      • A.6.4 #4 (1:31)
    • A.6.5 Continuous Aggregate Distributions ...
      • A.6.5 #1 (1:49)
      • A.6.5 #2 (1:59)
  • B.1 VaR and TVaR ... lessons ... min of video
    • B.1.1 Risk Measures ...
      • B.1.1 #1 (2:11)
      • B.1.1 #2 (1:32)
      • B.1.1 #3 (2:40)
      • B.1.1 #4 (1:33)
      • B.1.1 #6 (1:38)
      • B.1.1 #7 (1:02)
      • B.1.1 #8 (3:02)
    • B.1.2 Normal and Lognormal Distributions ...
      • B.1.2 #1 (2:19)
      • B.1.2 #2 (2:02)
      • B.1.2 #3 (2:38)
      • B.1.2 #4 (2:54)
      • B.1.2 #5 (3:45)
    • B.1.3 Deductibles ...
      • B.1.3 #1 (2:12)
      • B.1.3 #2 (3:12)
      • B.1.3 #3 (1:58)
      • B.1.3 #4 (8:56)
  • B.2 Coherence ... lessons ... min of video
    • B.2.1 Coherence ...
      • B.2.1 #1 (4:59)
      • B.2.1 #2 (0:31)
      • B.2.1 #3 (0:41)
      • B.2.1 #4 (3:38)
  • C.1 Maximum Likelihood Estimators ... lessons ... min of video
    • C.1.1 Maximum Likelihood Estimators ...
      • C.1.1 #1 (2:37)
      • C.1.1 #2 (1:32)
      • C.1.1 #3 (4:01)
      • C.1.1 #4 (1:44)
      • C.1.1 #5 (7:11)
      • C.1.1 #6 (1:53)
      • C.1.1 #7 (1:39)
      • C.1.1 #8 (1:42)
      • C.1.1 #9 (1:40)
      • C.1.1 #10 (2:43)
      • C.1.1 #11 (3:11)
      • C.1.1 #12 (1:53)
      • C.1.1 #13 (2:44)
      • C.1.1 #14 (4:04)
      • C.1.1 #15 (1:57)
      • C.1.1 #16 (1:09)
    • C.1.2 Special Cases ...
      • C.1.2 #1 (1:39)
    • C.1.3 Exponentials ...
      • C.1.3 #1 (1:03)
      • C.1.3 #2 (4:16)
      • C.1.3 #3 (1:16)
      • C.1.3 #4 (3:50)
    • C.1.4 Range Depends on Parameters ...
      • C.1.4 #1 (1:58)
    • C.1.5 Transformations ...
      • C.1.5 #1 (1:00)
      • C.1.5 #2 (1:10)
      • C.1.5 #3 (2:36)
      • C.1.5 #4 (1:54)
      • C.1.5 #5 (3:38)
      • C.1.5 #6 (2:52)
      • C.1.5 #7 (1:59)
  • C.2 Estimating Discrete Distributions ... lessons ... min of video
    • C.2.1 MLE for (a, b, 1) Distributions ...
      • C.2.1 #1 (0:28)
      • C.2.1 #2 (1:05)
      • C.2.1 #3 (5:18)
      • C.2.1 #4 (5:08)
    • C.2.2 Which (a, b, 1) Distribution? ...
      • C.2.2 #1 (2:20)
      • C.2.2 #2 (2:30)
      • C.2.2 #3 (1:00)
  • C.3 Variances of MLEs ... lessons ... min of video
    • C.3.1 Variances of MLEs ...
      • C.3.1 #1 (1:19)
      • C.3.1 #2 (1:22)
    • C.3.2 Fisher's Information ...
      • C.3.2 #1 (0:43)
      • C.3.2 #2 (2:36)
      • C.3.2 #3 (4:36)
      • C.3.2 #4 (2:12)
      • C.3.2 #5 (3:13)
      • C.3.2 #6 (2:57)
      • C.3.2 #7 (1:14)
    • C.3.3 Fisher's Information Continued ...
      • C.3.3 #1 (1:36)
    • C.3.4 Delta Method ...
      • C.3.4 #1 (5:30)
      • C.3.4 #2 (1:07)
      • C.3.4 #3 (5:02)
    • C.3.5 Delta Method Continued ...
      • C.3.5 #1 (4:45)
  • C.4 Hypothesis Testing ... lessons ... min of video
    • C.4.1 D(x) Plots ...
      • C.4.1 #1 (1:41)
      • C.4.1 #2 (2:18)
    • C.4.2 p-p plots ...
      • C.4.2 #1 (0:58)
      • C.4.2 #2 (0:25)
      • C.4.2 #3 (1:41)
    • C.4.3 Hypothesis Testing ...
      • C.4.3 #1 (0:43)
      • C.4.3 #2 (1:50)
      • C.4.3 #3 (2:44)
      • C.4.3 #4 (3:29)
      • C.4.3 #5 (1:42)
      • C.4.3 #6 (4:10)
      • C.4.3 #7 (1:37)
    • C.4.4 Kolmogorov-Smirnov ...
      • C.4.4 #1 (4:01)
      • C.4.4 #2 (2:32)
      • C.4.4 #3 (2:41)
      • C.4.4 #4 (3:07)
    • C.4.5 Chi-Square Tests I ...
      • C.4.5 #1 (4:08)
      • C.4.5 #2 (5:09)
      • C.4.5 #3 (3:43)
      • C.4.5 #4 (2:07)
      • C.4.5 #5 (2:19)
      • C.4.5 #6 (2:49)
    • C.4.7 Score Based Models ...
      • C.4.7 #1 (0:42)
    • C.4.8 Likelihood Ratio Test ...
      • C.4.8 #1 (1:22)
      • C.4.8 #2 (2:13)
      • C.4.8 #3 (3:21)
      • C.4.8 #4 (1:21)
      • C.4.8 #5 (0:35)
      • C.4.8 #6 (4:36)
      • C.4.8 #7 (3:08)
    • C.4.9 Non-Normal Confidence Intervals ...
      • C.4.9 #1 (4:13)
      • C.4.9 #2 (2:25)
      • C.4.9 #3 (5:00)
      • C.4.9 #4 (1:24)
      • C.4.9 #5 (4:20)
  • D.1 Classical Credibility ... lessons ... min of video
    • D.1.1 Credibility for Frequency ...
      • D.1.1 #1 (0:59)
      • D.1.1 #2 (1:21)
    • D.1.2 Credibility for Aggregate Distributions ...
      • D.1.2 #1 (1:18)
      • D.1.2 #2 (3:41)
      • D.1.2 #3 (1:06)
      • D.1.2 #4 (1:19)
      • D.1.2 #5 (4:02)
      • D.1.2 #6 (2:14)
      • D.1.2 #7 (1:26)
      • D.1.2 #8 (1:10)
      • D.1.2 #9 (2:14)
    • D.1.3 Partial Credibility ...
      • D.1.3 #1 (1:57)
      • D.1.3 #2 (3:42)
      • D.1.3 #3 (2:48)
      • D.1.3 #4 (1:37)
  • D.2 Bayesian Credibility ... lessons ... min of video
    • D.2.1 Discrete Bayesian Credibility ...
      • D.2.1 #1 (1:18)
      • D.2.1 #2 (3:51)
      • D.2.1 #3 (6:03)
      • D.2.1 #4 (4:28)
      • D.2.1 #5 (5:01)
      • D.2.1 #6 (3:15)
      • D.2.1 #14 (4:02)
    • D.2.2 Continuous Bayesian Credibility ...
      • D.2.2 #1 (2:27)
      • D.2.2 #2 (4:43)
      • D.2.2 #3 (1:52)
      • D.2.2 #4 (6:39)
      • D.2.2 #5 (3:35)
      • D.2.2 #6 (2:58)
      • D.2.2 #7 (3:59)
    • D.2.3 Poisson/Gamma ...
      • D.2.3 #1 (1:23)
      • D.2.3 #2 (1:51)
      • D.2.3 #3 (2:38)
      • D.2.3 #4 (2:47)
    • D.2.4 Binomial/Beta ...
      • D.2.4 #1 (3:29)
      • D.2.4 #2 (2:22)
      • D.2.4 #3 (3:07)
      • D.2.4 #4 (2:24)
    • D.2.6 Harder Examples ...
      • D.2.6 #1 (3:19)
      • D.2.6 #2 (4:00)
      • D.2.6 #3 (2:41)
      • D.2.6 #6 (2:54)
      • D.2.6 #7 (2:35)
  • D.3 Buhlmann Credibility ... lessons ... min of video
    • D.3.1 Buhlmann Credibility ...
      • D.3.1 #1 (3:01)
      • D.3.1 #2 (3:56)
      • D.3.1 #3 (2:13)
      • D.3.1 #4 (1:56)
      • D.3.1 #5 (3:29)
      • D.3.1 #6 (3:28)
    • D.3.2 Buhlmann with Discrete Distributions ...
      • D.3.2 #1 (2:52)
      • D.3.2 #2 (2:45)
      • D.3.2 #3 (3:09)
      • D.3.2 #4 (2:33)
      • D.3.2 #5 (5:00)
      • D.3.2 #6 (2:30)
    • D.3.3 Generalizations ...
      • D.3.3 #1 (4:27)
      • D.3.3 #2 (1:34)
    • D.3.5 Buhlmann as Linear Approximation of Bayesian ...
      • D.3.5 #1 (4:43)
    • D.3.6 Normal/Normal and Lognormal/Normal ...
      • D.3.6 #1 (3:43)
      • D.3.6 #2 (2:20)
      • D.3.6 #3 (2:35)
      • D.3.6 #4 (3:26)
      • D.3.6 #5 (4:35)
      • D.3.6 #6 (5:55)
      • D.3.6 #7 (3:25)
      • D.3.6 #8 (4:44)
      • D.3.6 #9 (4:00)
  • D.4 Empirical Credibility ... lessons ... min of video
    • D.4.1 Non-Parametric Credibility: Uniform Case ...
      • D.4.1 #1 (2:04)
      • D.4.1 #2 (3:22)
      • D.4.1 #3 (2:24)
    • D.4.2 Non-Parametric Credibility: General Case ...
      • D.4.2 #1 (4:23)
      • D.4.2 #2 (1:41)
      • D.4.2 #3 (2:00)
    • D.4.3 Semi-Parametric Credibility: Poisson Case ...
      • D.4.3 #1 (2:33)
      • D.4.3 #2 (1:50)
      • D.4.3 #3 (3:02)
  • TIA Practice Exams ... lessons ... min of video
    • Watch Me First! ...
      • Sample Exam Strategy Video (18:41)
    • Sample Exam 1 ...
      • Sample Exam 1 CBT format (allotted 3:30:00)
      • SE_01.P (Paper based format) (handout)
      • SE_01.S (PDF Solutions) (handout)
      • SE_01.01 (3:46)
      • SE_01.03 (2:04)
      • SE_01.04 (3:46)
      • SE_01.05 (2:58)
      • SE_01.06 (2:12)
      • SE_01.07 (3:57)
      • SE_01.09 (2:51)
      • SE_01.10 (3:17)
      • SE_01.11 (6:57)
      • SE_01.12 (2:00)
      • SE_01.14 (2:26)
      • SE_01.15 (1:42)
      • SE_01.18 (3:16)
      • SE_01.19 (5:04)
      • SE_01.21 (3:31)
      • SE_01.22 (1:27)
      • SE_01.25 (3:21)
      • SE_01.26 (2:35)
      • SE_01.27 (1:57)
      • SE_01.31 (2:19)
      • SE_01.32 (1:07)
      • SE_01.33 (2:17)
      • SE_01.34 (1:33)
      • SE_01.35 (3:11)
    • Sample Exam 2 ...
      • Sample Exam 2 CBT format (allotted 3:30:00)
      • SE_02.P (Paper based format) (handout)
      • SE_02.S (PDF solutions) (handout)
      • SE_02.01 (1:48)
      • SE_02.02 (5:36)
      • SE_02.03 (3:38)
      • SE_02.04 (4:40)
      • SE_02.06 (2:46)
      • SE_02.08 (4:23)
      • SE_02.09 (1:53)
      • SE_02.10 (4:09)
      • SE_02.11 (2:58)
      • SE_02.16 (4:18)
      • SE_02.19 (6:01)
      • SE_02.20 (3:20)
      • SE_02.21 (3:14)
      • SE_02.22 (4:03)
      • SE_02.23 (2:43)
      • SE_02.25 (3:06)
      • SE_02.26 (3:30)
      • SE_02.28 (3:50)
      • SE_02.32 (4:29)
      • SE_02.33 (3:32)
    • Sample Exam 3 ...
      • Sample Exam 3 CBT format (allotted 3:30:00)
      • SE_03.P (Paper based format) (handout)
      • SE_03.S (PDF solutions) (handout)
      • SE_03.01 (2:52)
      • SE_03.02 (2:38)
      • SE_03.03 (3:09)
      • SE_03.04 (3:49)
      • SE_03.05 (1:28)
      • SE_03.07 (3:29)
      • SE_03.08 (4:09)
      • SE_03.10 (3:20)
      • SE_03.12 (2:22)
      • SE_03.13 (1:38)
      • SE_03.16 (4:23)
      • SE_03.17 (2:20)
      • SE_03.18 (3:02)
      • SE_03.19 (1:44)
      • SE_03.20 (2:33)
      • SE_03.21 (2:51)
      • SE_03.24 (2:46)
      • SE_03.25 (3:29)
      • SE_03.26 (2:21)
      • SE_03.27 (4:18)
      • SE_03.28 (2:06)
      • SE_03.30 (2:43)
      • SE_03.31 (2:29)
      • SE_03.32 (2:06)
      • SE_03.34 (1:36)
      • SE_03.35 (2:11)
    • Sample Exam 4 ...
      • Sample Exam 4 CBT format (allotted 3:30:00)
      • SE_04.P (Paper based format) (handout)
      • SE_04.S (PDF Solutions) (handout)
      • SE_04.02 (5:24)
      • SE_04.03 (3:48)
      • SE_04.04 (1:26)
      • SE_04.08 (3:11)
      • SE_04.09 (2:59)
      • SE_04.10 (3:26)
      • SE_04.11 (2:20)
      • SE_04.12 (2:36)
      • SE_04.13 (6:30)
      • SE_04.14 (3:24)
      • SE_04.15 (3:03)
      • SE_04.16 (5:25)
      • SE_04.17 (3:55)
      • SE_04.18 (4:12)
      • SE_04.19 (3:32)
      • SE_04.21 (4:06)
      • SE_04.22 (3:49)
      • SE_04.24 (7:09)
      • SE_04.25 (2:35)
      • SE_04.27 (2:20)
      • SE_04.29 (3:04)
      • SE_04.30 (4:04)
      • SE_04.31 (4:45)
      • SE_04.33 (2:07)
      • SE_04.35 (2:15)
    • Sample Exam 5 ...
      • Sample Exam 5 CBT format (allotted 3:30:00)
      • SE_05.P (Paper based format and answers) (handout)
      • SE_05.S (PDF Solutions) (handout)
      • SE_05.01 (3:51)
      • SE_05.03 (2:45)
      • SE_05.06 (4:38)
      • SE_05.07 (4:15)
      • SE_05.08 (2:38)
      • SE_05.10 (3:07)
      • SE_05.14 (2:14)
      • SE_05.16 (4:17)
      • SE_05.17 (6:25)
      • SE_05.18 (1:53)
      • SE_05.20 (1:41)
      • SE_05.21 (3:07)
      • SE_05.24 (1:19)
      • SE_05.26 (3:44)
      • SE_05.28 (3:13)
      • SE_05.29 (1:36)
      • SE_05.30 (1:56)
      • SE_05.31 (2:03)
      • SE_05.32 (3:28)
      • SE_05.33 (3:19)
      • SE_05.34 (3:16)
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