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! →
Thu, 25 Apr 2019
I’m having some technical problems preventing this message from going out via email/course notification, so I apologize if you are seeing this multiple times. Thank you for using TIA to prepare for MAS-I. If you took the exam on Tuesday, I hope you passed! If you didn’t pass, then you might be eligible for a … Continue reading MAS-I first-draft solutions posted →
Mon, 25 Mar 2019
The summary sheet previously showed that the expected value of X_p was conditional on X_L being greater than d. This conditioning should have been either X_L >0 or X>d. I’ve corrected it to say X_L>0. This also affected one flashcard from C.3.6. I have that corrected in the flashcard app. Please change it by hand … Continue reading C.3 Summary sheet/flashcard correction →
Wed, 20 Mar 2019
The three new lessons C.3.4, C.3.5 and C.3.6, the summary sheet for C.3, problem sets, and flashcards for C.3 are now complete and available in the course. (This new content was announced first here: http://theinfiniteactuary.com/blogs/examS/2019/03/12/c-3-probability-for-insurance/)
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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Problem System Tour (sample) (7:45)
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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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2019 Exam Syllabus (From CAS) (handout)
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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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Printable Flash Cards (Retiring November 2019) ...
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All Flashcards 6 per page for printing (handout)
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All Flashcards 3 per page for Avery (handout)
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All Flashcards PDF (handout)
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All Flashcards JPEG (handout)
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A. Prerequisite Material ... lessons ... min of video
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Prerequisite Review ...
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A.1 Handouts (handout)
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A.1.1 Calculus Review (6:37)
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A.1.2 Probability Review (37:14)
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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.4.1 Life Tables and the ILT (17:23)
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B.4.4 Whole Life Insurance (20:00)
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B.4.5 Whole Life Annuities (21:48)
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B.4.6 Term Insurance (12:05)
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B.4.8 Level Annual Premiums (14:20)
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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.2.1 Hypothesis Testing (34:57)
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C.2.4 Comparing Populations (29:20)
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C.2.5 Tests for Variance (16:05)
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C.2.6 Confidence Intervals (36:51)
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C.2.7 Other Chi-Square Tests (26:07)
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C.2.8 Likelihood Ratio Test (39:52)
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C.2.9 Kolmogorov-Smirnov Test (20:21)
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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 (13:08)
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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 Classical Linear Models ...
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D.1.0 Statistical Learning (20:42)
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D.1.3 Categorical Variables (30:35)
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D.1.4 General Linear Models (27:48)
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D.2. Generalized Linear Models ...
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D.2.1 GLM Overview (8:25)
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D.3 Model Testing and Estimation ...
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D.3.1 Score Statistic (31:11)
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D.3.2 Wald Statistic (17:15)
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D.3.4 Model Estimation (20:29)
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D.3.6 Testing with Deviance (39:49)
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D.4 Model Evaluation ...
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D.4.1 Residuals (19:36)
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D.4.3 Goodness of Fit Statistics (23:16)
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D.4.4 Cross Validation (28:19)
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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 (38:29)
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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 (19:04)
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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 (24:19)
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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 (20:05)
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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 (8:33)
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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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Simulation (20:59)
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Statistics Review ...
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General Linear Models Review ...
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Classical Linear Models Review (42:01)
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Generalized Linear Models Review (32:06)
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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.1.3 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.1.5 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 (2:29)
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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.2 Continuous Multiple Lives/Decrements ... lessons ... min of video
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B.2.1 Hazard Rate ...
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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.2.8 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 Future Lifetime Moments - Discrete Case ...
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B.4.3 Life Contingent Cash Flows ...
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B.4.4 Whole Life Insurance ...
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B.4.5 Whole Life Annuities ...
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B.4.6 Term Insurance ...
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B.4.7 Endowment Insurance and Temporary Annuities ...
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B.4.8 Level Annual Premiums ...
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B.4.9 Joint-Life and Last-Survivor Status ...
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B.4.10 Fractional Ages, Adjusted Mortality ...
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B.4.11 Multiple Decrement Table ...
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B.4.11 #1 (2:09)
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B.4.11 #2 (2:16)
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B.4.11 #3 (1:26)
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B.4.11 #4 (1:36)
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B.4.11 #5 (5:03)
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B.4.11 #6 (2:28)
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B.4.11 #7 (3:17)
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B.4.11 #8 (2:53)
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B.4.11 #9 (3:02)
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B.4.11 #10 (3:39)
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B.4.11 #11 (1:18)
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B.4.11 #12 (2:13)
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B.4.11 #13 (5:32)
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B.4.11 #14 (3:36)
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B.4.11 #15 (3:20)
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B.4.11 #16 (2:41)
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B.4.11 #17 (2:21)
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B.4.11 #18 (2:58)
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B.4.11 #19 (3:44)
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B.4.11 #20 (3:15)
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B.5 Simulation 0 lessons 0 min of video
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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 (2:37)
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C.1.4 #2 (0:48)
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C.1.4 #3 (2:21)
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C.1.4 #4 (1:51)
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C.1.4 #5 (2:36)
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C.1.4 #6 (2:20)
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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 (1:02)
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C.1.4 #12 (3:05)
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C.1.4 #13 (1:23)
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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 (2:53)
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C.1.4 #26 (7:11)
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C.1.4 #27 (2:28)
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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.2 Hypothesis Testing ... lessons ... min of video
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C.2.1 Hypothesis Testing ...
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C.2.2 Tests for the mean: ``Known'' variance ...
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C.2.2 #1 (1:50)
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C.2.2 #2 (2:28)
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C.2.2 #3 (4:12)
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C.2.2 #4 (2:51)
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C.2.2 #5 (7:22)
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C.2.2 #6 (6:28)
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C.2.2 #7 (7:18)
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C.2.2 #8 (4:51)
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C.2.2 #9 (2:09)
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C.2.2 #10 (1:43)
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C.2.2 #11 (0:50)
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C.2.2 #12 (1:14)
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C.2.2 #13 (0:58)
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C.2.2 #14 (2:06)
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C.2.2 #15 (3:43)
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C.2.2 #16 (11:15)
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C.2.2 #17 (3:55)
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C.2.2 #18 (4:07)
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C.2.2 #19 (4:44)
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C.2.2 #20 (4:24)
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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 Likelihood Ratio Test ...
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C.2.9 Kolmogorov-Smirnov Test ...
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C.3 Order Statistics ... lessons ... min of video
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C.3.1 Order Statistics ...
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C.3.2 Uniform and Exponential Order Stats ...
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C.3.2 #1 (2:27)
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C.3.2 #2 (2:18)
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C.3.2 #3 (2:39)
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C.3.2 #4 (13:20)
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C.3.2 #5 (2:46)
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C.3.2 #6 (7:51)
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C.3.2 #7 (4:01)
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C.3.2 #8 (4:50)
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C.3.2 #9 (9:15)
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C.3.2 #10 (0:59)
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C.3.2 #11 (2:12)
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C.3.2 #12 (0:47)
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C.3.2 #13 (9:20)
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C.3.2 #14 (3:27)
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C.3.2 #15 (5:45)
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C.3.2 #16 (1:45)
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C.3.2 #17 (4:43)
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C.3.2 #18 (3:16)
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C.3.2 #19 (2:02)
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C.3.2 #20 (4:14)
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C.3.2 #21 (2:28)
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C.3.2 #22 (2:29)
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C.3.2 #23 (2:29)
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C.3.2 #24 (1:59)
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C.3.2 #25 (2:06)
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C.3.2 #26 (1:58)
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D.1 Classical Linear Models ... lessons ... min of video
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D.1.1 Single Variable Linear Regression ...
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D.1.2 Multivariable Linear Regression ...
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D.1.3 Categorical Variables ...
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D.1.4 General Linear Models ...
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D.2 Generalized Linear Models ... lessons ... min of video
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D.2.2 Exponential Families, Redux ...
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D.2.3 Continuous Response Distributions ...
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D.2.4 Categorical Response: Binary ...
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D.2.5 Categorical Response: Multinomial ...
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D.2.6 Categorical Response: Count Data ...
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D.3 Model Testing and Estimation ... lessons ... min of video
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D.3.1 Score Statistic ...
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D.3.2 Wald Statistic ...
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D.3.3 Likelihood Ratio Statistic: Deviance ...
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D.3.4 Model Estimation ...
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D.3.5 Testing with the Wald Statistic ...
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D.3.6 Testing with Deviance ...
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D.3.7 Testing General Linear Models ...
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D.4 Model Evaluation ... lessons ... min of video
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D.5 Model Selection and Regularization ... lessons ... min of video
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D.6 Generalized Additive Models 0 lessons 0 min of video
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D.7 Modeling with R ... lessons ... min of video
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E.1 Time Series Basics ... lessons ... min of video
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E.1.1 Time Series ...
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E.1.2 Decomposition ...
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E.1.3 Correlation ...
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E.1.4 Cross-Correlation ...
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E.2 Time Series Models ... lessons ... min of video
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E.2.1 Random Walks ...
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E.2.2 Autoregressive Models ...
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E.2.3 Moving Average Models ...
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E.2.4 ARMA Models ...
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E.2.5 Non-seasonal ARIMA Models ...
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E.2.6 Seasonal ARIMA Models ...
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E.3 Time Series Regression ... lessons ... min of video
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Watch Me First! ... lessons ... min of video
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Sample Exams Strategy (Updated for Spring 2019) ...
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Sample Exam 1 ... lessons ... min of video
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Questions ...
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