Exam MAS-I
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Thu, 17 Nov 2016
Welcome to the Announcements Tab for the TIA MAS-I Seminar. Here you will primarily find records of important updates, changes, and corrections to the seminar content. Any old posts here do not need to be considered for new users of the seminar – if there are any old posts that need to be considered again, … Continue reading Welcome to the MAS-I Announcements Page! →
Sat, 27 Feb 2021
Yesterday, Pearsonvue.com/CAS got an update that includes a direct link to the Sample Spreadsheet. So now you can go directly to the spreadsheet to practice and you don’t have to click all the way through the Demo Exam’s 15 introductory screens if all you want to do is test something in the Exam Spreadsheet Scratchpad. … Continue reading Direct Link to CAS Demo Exam Sample Spreadsheet →
Fri, 19 Feb 2021
I have completed updating the C.2 lessons, summary sheet and flashcards. This also included updating the problems, solutions and video solutions as well. The update both added the use of spreadsheet commands to do probability and critical value computations throughout, and also made significant improvements to the explanations and the choices regarding what to … Continue reading C.2 Updates complete →
Fri, 15 Jan 2021
With the addition of a spreadsheet tool for use during the new CBT style MAS-I, we now have access to functions that can precisely compute many probability distribution values. Last fall, I created a series of quick example lessons that live in the prerequisite material section of the course to illustrate how several of these … Continue reading C.2 lesson updates underway →
Searches titles below, use an * (asterisk) for any character
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Before You Begin ... lessons ... min of video
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***Start Here!*** ...
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New to TIA? Take a tour. ...
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Practice App Tour (15:24)
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Forum Tour (sample) (5:58)
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You Failed. Now what? (12:00)
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Schedule, Syllabus and Study Notes ...
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Customizable Study Schedule (handout)
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Video Player Keyboard Shortcuts (sample) (handout)
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2021 Exam Syllabus (From CAS) (handout)
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Exam Tables Overview (17:28)
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Poisson Processes Study Note (From CAS) (handout)
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Life Contingencies Study Note (From CAS) (handout)
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GLM Study Note (From CAS) (handout)
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Knowledge Mapping (From CAS) (handout)
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Formula Sheets ...
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Cas MAS-I Exam Tables (handout)
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All Sheets in 1 zip file (handout)
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A.1 Formula Sheet (handout)
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B.1 Formula Sheet (sample) (handout)
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B.2 Formula Sheet (handout)
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B.3 Formula Sheet (handout)
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B.4 Formula Sheet (handout)
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B.5 Formula Sheet (handout)
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C.1 Formula Sheet (handout)
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C.2 Formula Sheet (handout)
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C.3 Formula Sheet (handout)
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D.1 Formula Sheet (handout)
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D.2 Formula Sheet (handout)
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D.3 Formula Sheet (handout)
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D.4 Formula Sheet (handout)
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D.5 Formula Sheet (handout)
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D.6 Formula Sheet (handout)
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E.1 Formula Sheet (handout)
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E.2 Formula Sheet (handout)
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E.3 Formula Sheet (handout)
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A. Prerequisite Material ... lessons ... min of video
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Prerequisite Review ...
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How to use these lessons (1:55)
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Derivatives: Basic Formulas (7:27)
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Derivatives: Chain Rule (6:39)
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Derivatives: Product Rule (5:10)
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Integration: Basic Formulas (6:27)
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Integration: Substitution (6:12)
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Integration by Parts (3:57)
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Poisson Random Variables (5:48)
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Continuous Random Variables (7:26)
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Continuous Moments (5:33)
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Uniform Random Variables (6:11)
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Normal Distribution (11:27)
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Normal Approximation (9:09)
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Continuity Correction (5:57)
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Covariance and Correlation (9:53)
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Conditional Distributions (7:46)
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Spreadsheet Examples ...
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About these lessons (1:21)
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Basic Formulas (13:06)
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Matrix Multiplication (5:15)
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Systems of linear equations (6:36)
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Actuarial Present Value (4:23)
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Binomial Distribution (4:23)
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Percentiles (2:19)
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T-distribution (9:22)
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F-distribution (10:00)
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Chi-square distribution (10:31)
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Kolmogorov-Smirnov Statistic (3:09)
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Linear Regression (4:14)
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Autocorrelation (7:48)
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Time Series Forecasts (2:37)
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B. Stochastic Processes ... lessons ... min of video
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B.1 Poisson Processes ...
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B.2 Continuous Multiple Lives/Decrements ...
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B.2.1 Hazard Rate (26:36)
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B.2.2 Joint-Life Status (18:59)
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B.2.3 Last-Survivor Status (15:01)
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B.2.4 Multiple Decrements (12:42)
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B.2.6 The Bridge System (35:44)
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B.2.7 The k out of n system (22:18)
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B.2.8 The Random Graph (22:15)
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B.2.9 Expected Lifetimes (21:26)
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B.3 Markov Chains ...
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B.3.1 Discrete Markov Chains (22:31)
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B.3.3 Long Run Behavior (26:21)
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B.3.4 Applications 1 (22:41)
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B.4 Life Contingencies ...
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B.4.2 Life Tables Applications (25:54)
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B.4.3 Whole Life Insurance (28:08)
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B.4.4 Insurance Examples (24:17)
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B.4.5 Whole Life Annuities (17:52)
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B.4.6 Annuities Examples (25:21)
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B.4.7 Premiums (22:24)
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B.5 Simulation ...
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B.5.2 Inverse Transform Method (10:51)
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C. Statistics ... lessons ... min of video
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C.1 Parameter Estimation ...
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C.1.1 Estimator Basics (sample) (19:28)
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C.1.6 Variance of MLE (18:34)
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C.1.7 Exponential Family (31:42)
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C.1.8 Method of Moments (15:53)
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C.1.9 Percentile Matching (20:47)
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C.1.10 Kernel Density Estimation (31:32)
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C.2 Hypothesis Testing ...
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C.2.2 Tests for the mean, Part 1 (33:33)
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C.2.3 Tests for the mean, Part 2 (26:31)
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C.2.4 Comparing Populations (35:33)
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C.2.5 Tests for Variance (23:08)
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C.2.6 Confidence Intervals (25:29)
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C.2.7 Other Chi-Square Tests (39:39)
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C.2.9 Kolmogorov-Smirnov Test (18:24)
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C.3 Probability for Insurance ...
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C.3.1 Order Statistics (24:38)
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C.3.3 Mixtures (17:24)
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C.3.4 Transformations (13:04)
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C.3.5 Tail Properties (26:23)
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C.3.6 Policy Adjustments (25:25)
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D. Extended Linear Models ... lessons ... min of video
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D.1 Linear Regression ...
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D.1.1 Statistical Learning (21:15)
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D.1.2 Minimal and Maximal Models (29:29)
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D.1.4 Variations on Regression (27:17)
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D.1.5 Multiple Linear Regression (28:08)
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D.1.7 Two Factor ANOVA (34:35)
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D.1.8 General Linear Models (21:53)
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D.2 Generalized Linear Models ...
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D.2.0 Intro to GLM (9:15)
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D.2.1 Model Definition (17:42)
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D.2.2 Exponential Family for GLM (30:13)
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D.2.3 Model Estimation (39:01)
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D.2.4 Continuous Response Models (17:35)
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D.2.5 Binary Response Data (22:52)
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D.2.7 Poisson Count Models (14:21)
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D.3 Model Testing ...
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D.3.0 Intro to GLM Testing (3:35)
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D.3.2 Deviance Testing (25:35)
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D.4 Model Evaluation ...
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D.4.1 Residuals (20:21)
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D.4.3 Goodness of Fit Statistics (23:16)
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D.4.4 Cross Validation (28:10)
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D.4.5 Bootstrap (15:00)
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D.5 Model Selection ...
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D.5.1 Subset Selection (23:22)
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D.5.2 High-Dimension Models (19:11)
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D.5.3 Shrinkage Methods (30:18)
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D.6 Generalized Additive Models ...
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D.6.2 Regression Splines (25:31)
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D.7 Modeling with R ...
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D.7.1 Continuous Response (38:56)
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D.7.2 Categorical Response (28:20)
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D.7.3 Count Data (25:56)
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D.7.5 GAM Part 1 (19:57)
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D.7.5 GAM Part 2 (16:02)
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E. Time Series ... lessons ... min of video
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E.1 Time Series Basics ...
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E.1.1 Time Series (19:03)
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E.1.2 Decomposition (16:53)
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E.1.3 Correlation (27:35)
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E.1.4 Cross-Correlation (17:14)
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E.2 Time Series Models ...
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E.2.1 Random Walks (31:47)
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E.2.2 Autoregressive Models (24:18)
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E.2.3 Moving Average Models (19:41)
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E.2.4 ARMA Models (23:15)
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E.2.5 Non-seasonal ARIMA Models (17:09)
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E.2.6 Seasonal ARIMA Models (20:06)
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E.3 Time Series Regression ...
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E.3.1 Regression Modelling (16:13)
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E.3.2 Seasonal Regression (24:46)
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What to do after you finish the lessons ... lessons ... min of video
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Managing the work problems study phase ...
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The Last Lesson (5:05)
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Review Lessons ... lessons ... min of video
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Stochastic Processes Review ...
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Poisson Processes Review (25:28)
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Continuous/Multiple Lives Review (37:23)
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Markov Chains Review (21:29)
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Life Contingencies Review (41:37)
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Simulation (20:59)
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Statistics Review ...
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Parameter Estimation Review (33:23)
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Hypothesis Testing Review (42:49)
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Probability for Insurance Review (35:46)
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Extended Linear Models Review ...
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Linear Regression Review, Part I (19:33)
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General Linear Models Review (39:07)
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Model Testing Review (24:41)
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Model Evaluation Review (33:22)
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General Additive Models Review (23:04)
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Time Series Review ...
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Time Series Basics Review (27:12)
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Time Series Models Review (31:22)
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Time Series Regression Review (19:16)
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Start Here! ... lessons ... min of video
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How I suggest that you use the Solutions Tab ...
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B.1 Poisson Processes ... lessons ... min of video
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B.1.1 Exponential Random Variables Part 1 ...
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B.1.2 Exponential Random Variables Part 2 ...
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B.1.2 #1 (1:42)
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B.1.2 #2 (1:26)
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B.1.2 #3 (2:15)
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B.1.2 #4 (7:26)
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B.1.2 #5 (5:10)
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B.1.2 #7 CAS S Fall 2016 #5 (4:08)
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B.1.2 #8 CAS S Fall 2016 #7 (2:09)
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B.1.2 #9 CAS S Fall 2017 #6 (3:32)
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B.1.2 #10CAS S Fall 2017 #7 (4:40)
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B.1.3 What is a Poisson Process? ...
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B.1.4 Waiting times, Classification ...
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B.1.4 #1 (2:28)
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B.1.4 #2 (1:41)
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B.1.4 #3 (1:34)
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B.1.4 #4 (1:38)
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B.1.4 #5 (1:44)
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B.1.4 #6 (4:14)
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B.1.4 #7 (1:34)
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B.1.4 #8 (3:56)
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B.1.4 #9 (5:08)
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B.1.4 #10 (2:23)
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B.1.4 #11 (3:24)
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B.1.4 #12 (3:38)
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B.1.4 #13 (6:10)
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B.1.4 #14 (5:59)
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B.1.4 #15 (6:49)
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B.1.4 #16 (3:31)
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B.1.4 #17 (5:01)
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B.1.4 #18 (2:37)
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B.1.4 #19 (3:52)
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B.1.4 #20 (3:22)
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B.1.4 #21 (1:36)
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B.1.4 #22 (4:01)
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B.1.4 #23 (1:25)
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B.1.4 #24 (1:52)
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B.1.4 #25 (4:27)
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B.1.4 #26 (0:40)
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B.1.4 #27 (7:41)
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B.1.4 #28 (1:48)
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B.1.4 #29 (4:58)
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B.1.4 #30 (1:45)
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B.1.4 #31 (1:28)
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B.1.4 #32 CAS S Fall 2015 #1 (1:03)
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B.1.4 #35 CAS S Fall 2016 #1 (3:37)
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B.1.4 #36 CAS S Fall 2016 #2 (2:50)
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B.1.4 #39 CAS S Fall 2017 #1 (4:09)
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B.1.4 #40 CAS S Fall 2017 #2 (1:59)
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B.1.5 Nonhomogeneous Poisson Processes ...
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B.1.6 Compound Poisson Processes ...
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B.1.6 #1 (1:49)
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B.1.6 #2 (3:36)
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B.1.6 #3 (2:36)
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B.1.6 #4 (5:43)
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B.1.6 #5 (7:33)
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B.1.6 #6 (3:35)
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B.1.6 #7 (4:20)
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B.1.6 #8 (2:46)
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B.1.6 #9 (2:24)
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B.1.6 #10 (2:10)
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B.1.6 #11 (4:09)
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B.1.6 #12 (6:44)
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B.1.6 #13 (4:54)
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B.1.6 #14 (6:15)
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B.1.6 #15 (3:58)
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B.1.6 #16 (2:00)
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B.1.6 #17 (2:05)
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B.1.6 #18 (5:45)
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B.1.6 #19 (4:36)
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B.1.6 #20 (7:54)
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B.1.6 #21 (3:47)
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B.1.6 #22 (2:04)
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B.1.6 #23 CAS S Fall 2015 #4 (5:35)
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B.1.6 #25 CAS S Fall 2016 #4 (2:39)
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B.1.6 #27 CAS S Fall 2017 #4 (5:49)
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B.2 Continuous Multiple Lives/Decrements ... lessons ... min of video
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B.2.1 Hazard Rate ...
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B.2.1 #1 (1:10)
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B.2.1 #2 (1:25)
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B.2.1 #3 (3:56)
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B.2.1 #4 (0:39)
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B.2.1 #5 (2:37)
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B.2.1 #6 (2:13)
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B.2.1 #7 (2:56)
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B.2.1 #8 (4:59)
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B.2.1 #9 (4:58)
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B.2.1 #10 (1:26)
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B.2.1 #11 (1:50)
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B.2.1 #12 (4:27)
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B.2.1 #13 (4:35)
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B.2.1 #14 (4:09)
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B.2.1 #15 (3:24)
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B.2.1 #16 (9:10)
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B.2.1 #17 (4:34)
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B.2.1 #18 (2:29)
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B.2.1 #19 (1:49)
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B.2.1 #20 (0:57)
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B.2.1 #22 CAS S Fall 2016 #6 (1:13)
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B.2.1 #23 (2:00)
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B.2.2 Joint-Life Status ...
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B.2.3 Last-Survivor Status ...
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B.2.4 Multiple Decrements ...
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B.2.5 Multi-Component Joint-Life and Last-Survivor ...
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B.2.6 The Bridge System ...
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B.2.7 The k out of n system ...
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B.2.7 #1 (0:26)
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B.2.7 #2 (1:40)
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B.2.7 #3 (4:05)
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B.2.7 #4 (6:22)
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B.2.7 #5 (7:19)
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B.2.7 #6 CAS S Fall 2016 #10 (1:03)
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B.2.7 #8 CAS S Fall 2017 #8 (2:12)
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B.2.8 The Random Graph ...
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B.2.9 Expected Lifetimes ...
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B.3 Markov Chains ... lessons ... min of video
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B.3.1 Discrete Markov Chains ...
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B.3.1 #1 (3:54)
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B.3.1 #2 (3:32)
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B.3.1 #3 (3:22)
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B.3.1 #4 (3:13)
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B.3.1 #5 (2:23)
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B.3.1 #6 (3:59)
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B.3.1 #7 (7:18)
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B.3.1 #8 (4:34)
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B.3.1 #9 (2:35)
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B.3.1 #10 (3:11)
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B.3.1 #11 (4:44)
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B.3.1 #12 (1:41)
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B.3.1 #13 (4:48)
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B.3.1 #14 (2:47)
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B.3.1 #15 (3:07)
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B.3.1 #16 (6:14)
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B.3.1 #17 (7:54)
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B.3.1 #18 (7:41)
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B.3.1 #19 (0:57)
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B.3.1 #20 (7:31)
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B.3.1 #21 (5:58)
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B.3.1 #22 (1:55)
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B.3.2 Classification of States ...
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B.3.3 Long Run Behavior ...
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B.3.4 Applications 1 ...
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B.3.5 Applications 2: Branching Processes ...
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B.4 Life Contingencies ... lessons ... min of video
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B.4.1 Life Tables and the ILT ...
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B.4.2 Life Tables Applications ...
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B.4.3 Whole Life Insurance ...
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B.4.4 Insurance Examples ...
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B.4.5 Whole Life Annuities ...
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B.4.6 Annuities Examples ...
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B.4.7 Premiums ...
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B.5 Simulation ... lessons ... min of video
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B.5.1 Simulating Uniform Random Numbers ...
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B.5.2 Inverse Transform Method ...
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B.5.3 Acceptance-Rejection Method ...
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C.1 Parameter Estimation ... lessons ... min of video
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C.1.1 Estimator Basics ...
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C.1.2 Comparing Estimators: Mean and Variance ...
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C.1.3 Comparing Estimators: Likelihood and Sufficiency ...
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C.1.4 The Maximum Likelihood Estimator ...
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C.1.4 #1 (2:12)
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C.1.4 #2 (1:08)
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C.1.4 #3 (4:29)
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C.1.4 #4 (3:48)
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C.1.4 #5 (3:29)
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C.1.4 #6 (3:00)
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C.1.4 #7 (4:35)
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C.1.4 #8 (4:23)
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C.1.4 #9 (3:16)
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C.1.4 #10 (3:21)
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C.1.4 #11 (5:30)
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C.1.4 #12 (4:16)
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C.1.4 #13 (1:59)
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C.1.4 #14 (2:04)
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C.1.4 #15 (1:50)
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C.1.4 #16 (3:53)
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C.1.4 #17 (3:38)
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C.1.4 #18 (2:10)
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C.1.4 #19 (2:22)
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C.1.4 #20 (5:12)
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C.1.4 #21 (6:54)
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C.1.4 #22 (2:26)
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C.1.4 #23 (3:32)
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C.1.4 #24 (1:55)
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C.1.4 #25 (3:20)
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C.1.4 #26 (9:02)
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C.1.4 #27 (2:16)
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C.1.5 Advanced Likelihood Functions ...
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C.1.6 Variance of MLE ...
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C.1.7 Exponential Family ...
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C.1.8 Method of Moments ...
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C.1.9 Percentile Matching ...
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C.1.10 Kernel Density Estimation ...
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C.2 Hypothesis Testing ... lessons ... min of video
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C.2.1a Hypothesis Testing, Part 1 ...
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C.2.1a #1 (7:17)
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C.2.1a #2 (5:48)
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C.2.1a #3 (4:18)
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C.2.1a #4 (3:24)
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C.2.1a #5 (3:16)
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C.2.1a #6 (4:10)
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C.2.1a #7 (3:31)
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C.2.1a #13 (6:17)
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C.2.1a #14 (5:53)
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C.2.1a #15 (1:33)
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C.2.1b Hypothesis Testing, Part 2 ...
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C.2.2 Tests for the mean: ``Known'' variance ...
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C.2.3 Tests for the mean: ``Unknown'' Variance ...
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C.2.4 Comparing Populations ...
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C.2.5 Tests for Variance ...
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C.2.6 Confidence Intervals ...
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C.2.7 Other Chi-Square Tests ...
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C.2.8 part I: Neyman-Pearson Test ...
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C.2.8 part I #1 (2:57)
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C.2.8 part I #2 (1:52)
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C.2.8 part I #3 (8:20)
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C.2.8 part I #4 (6:59)
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C.2.8 part I #5 (6:54)
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C.2.8 part I #6 (4:09)
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C.2.8 part I #7 (2:52)
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C.2.8 part I #8 (2:50)
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C.2.8 part I #9 (3:58)
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C.2.8 part II: Likelihood Ratio Test ...
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C.2.8 part II #1 (2:37)
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C.2.8 part II #2 (4:25)
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C.2.8 part II #3 (4:15)
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C.2.8 part II #4 (8:53)
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C.2.8 part II #5 (4:05)
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C.2.8 part II #6 (5:12)
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C.2.8 part II #7 (4:03)
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C.2.9 Kolmogorov-Smirnov Test ...
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C.3 Probability for Insurance ... lessons ... min of video