Exam MAS-I

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Welcome to the MAS-I Announcements Page!

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 →

D.2 Lesson update rollout has begun

Fri, 31 Jan 2020

I just posted the new intro lesson to D.2, and also the placeholders for the rest of the newly updated D.2 lessons. I’ve been delayed getting these lessons completed this month, but I am now ready to record, and hope to launch a new lesson every day or so for the next week or two. … Continue reading →

New D.1 lessons complete

Thu, 02 Jan 2020

I’ve just finished moving over the practice problems from the old to the new D.1 lessons, so these updated lessons are now complete. There are a couple of new lessons that don’t yet have problems associated with them. I do plan to add some problems for those, but there is no time frame for that … Continue reading →

Fall 2019 Final Answer Key

Wed, 04 Dec 2019

The CAS has now posted the final answer key for the Fall 2019 MAS-I exam, so I have updated the “answer key and handwritten solutions” file posted in the Sample exams tab for the Fall 2019 exam accordingly. As I mentioned in an email to the exam takers for Fall, I submitted an appeal to … Continue reading →

Before You Begin ... lessons ... min of video
- ***Start Here!*** ...
  - How to use the seminar (sample) (3:49)
- New to TIA? Take a tour. ...
  - How to Prepare for actuarial exams (sample) (15:41)
  - Problem System Tour (sample) (7:45)
  - Forum Tour (sample) (5:58)
  - You Failed. Now what? (12:00)
- Schedule, Syllabus and Study Notes ...
  - Customizable Study Schedule (handout)
  - Video Player Keyboard Shortcuts (sample) (handout)
  - 2019 Exam Syllabus (From CAS) (handout)
  - Exam Tables Overview (17:28)
  - Poisson Processes Study Note (From CAS) (handout)
  - Life Contingencies Study Note (From CAS) (handout)
  - GLM Study Note (From CAS) (handout)
  - Knowledge Mapping (From CAS) (handout)
- Formula Sheets ...
  - Cas MAS-I Exam Tables (handout)
  - All Sheets in 1 zip file (handout)
  - A.1 Formula Sheet (handout)
  - B.1 Formula Sheet (sample) (handout)
  - B.2 Formula Sheet (handout)
  - B.3 Formula Sheet (handout)
  - B.4 Formula Sheet (handout)
  - B.5 Formula Sheet (handout)
  - C.1 Formula Sheet (handout)
  - C.2 Formula Sheet (handout)
  - C.3 Formula Sheet (handout)
  - D.1 Formula Sheet (handout)
  - D.2 Formula Sheet (handout)
  - D.3 Formula Sheet (handout)
  - D.4 Formula Sheet (handout)
  - D.5 Formula Sheet (handout)
  - D.6 Formula Sheet (handout)
  - E.1 Formula Sheet (handout)
  - E.2 Formula Sheet (handout)
  - E.3 Formula Sheet (handout)
A. Prerequisite Material ... lessons ... min of video
- Prerequisite Review ...
  - A.1 Handouts (handout)
  - A.1.1 Calculus Review (6:37)
  - A.1.2 Probability Review (37:14)
B. Stochastic Processes ... lessons ... min of video
- B.1 Poisson Processes ...
  - B.1.1 Exponential Random Variables Part 1 (27:47)
  - B.1.2 Exponential Random Variables Part 2 (22:17)
  - B.1.3 What is a Poisson Process? (sample) (18:13)
  - B.1.4 Waiting Times, Classification (25:15)
  - B.1.5 Nonhomogeneous Poisson Processes (17:03)
  - B.1.6 Compound Poisson Processes (22:55)
- B.2 Continuous Multiple Lives/Decrements ...
  - B.2.1 Hazard Rate (26:36)
  - B.2.2 Joint-Life Status (18:59)
  - B.2.3 Last-Survivor Status (15:01)
  - B.2.4 Multiple Decrements (12:42)
  - B.2.5 Multi-Component Joint-Life and Last-Survivor (21:42)
  - B.2.6 The Bridge System (35:44)
  - B.2.7 The k out of n system (22:18)
  - B.2.8 The Random Graph (22:15)
  - B.2.9 Expected Lifetimes (21:26)
- B.3 Markov Chains ...
  - B.3.1 Discrete Markov Chains (22:31)
  - B.3.2 Classification of States (sample) (20:42)
  - B.3.3 Long Run Behavior (26:21)
  - B.3.4 Applications 1 (22:41)
  - B.3.5 Applications 2: Branching Processes (18:32)
- B.4 Life Contingencies (Updated November 2019) ...
  - B.4.0 Intro to Life Contingencies for MAS-I (7:30)
  - B.4.1 Life Tables and the Illustrative Life Table (ILT) (31:25)
  - B.4.2 Life Tables Applications (25:54)
  - B.4.3 Whole Life Insurance (28:08)
  - B.4.4 Insurance Examples (24:17)
  - B.4.5 Whole Life Annuities (17:52)
  - B.4.6 Annuities Examples (25:00)
  - B.4.7 Premiums (22:24)
- B.5 Simulation ...
  - B.5.1 Simulating Uniform Random Numbers (17:37)
  - B.5.2 Inverse Transform Method (10:51)
  - B.5.3 Acceptance-Rejection Method (31:41)
C. Statistics ... lessons ... min of video
- C.1 Parameter Estimation ...
  - C.1.1 Estimator Basics (sample) (19:28)
  - C.1.2 Comparing Estimators: Mean and Variance (23:01)
  - C.1.3 Comparing Estimators: Likelihood and Sufficiency (26:22)
  - C.1.4 The Maximum Likelihood Estimator (30:38)
  - C.1.5 Advanced Likelihood Functions (26:40)
  - C.1.6 Variance of MLE (18:34)
  - C.1.7 Exponential Family (31:42)
  - C.1.8 Method of Moments (15:53)
  - C.1.9 Percentile Matching (20:47)
  - C.1.10 Kernel Density Estimation (31:32)
- C.2 Hypothesis Testing ...
  - C.2.1 Hypothesis Testing (34:57)
  - C.2.2 Tests for the mean: ``Known'' variance (32:04)
  - C.2.3 Tests for the mean: ``Unknown'' Variance (25:45)
  - C.2.4 Comparing Populations (29:20)
  - C.2.5 Tests for Variance (16:05)
  - C.2.6 Confidence Intervals (36:51)
  - C.2.7 Other Chi-Square Tests (26:07)
  - C.2.8 Likelihood Ratio Test (39:52)
  - C.2.9 Kolmogorov-Smirnov Test (20:21)
- C.3 Probability for Insurance ...
  - C.3.1 Order Statistics (24:38)
  - C.3.2 Uniform and Exponential Order Stats (17:53)
  - C.3.3 Mixtures (17:24)
  - C.3.4 Transformations (13:04)
  - C.3.5 Tail Properties (26:23)
  - C.3.6 Policy Adjustments (25:25)
D. Extended Linear Models ... lessons ... min of video
- D.1 Linear Regression (Updated December 2019) ...
  - D.1.0 Into to Extended Linear Models (11:31)
  - D.1.1 Statistical Learning (21:15)
  - D.1.2 Minimal and Maximal Models (29:29)
  - D.1.3 Single Variable Linear Regression (41:49)
  - D.1.4 Variations on Regression (27:17)
  - D.1.5 Multiple Linear Regression (28:08)
  - D.1.6 One Categorical Predictor - One-Way ANOVA (38:58)
  - D.1.7 Two Factor ANOVA (34:35)
  - D.1.8 General Linear Models (21:53)
- D.1 Classical Linear Models (Old lessons) ...
  - D.1.0 Statistical Learning (20:42)
  - D.1.1 Single Variable Linear Regression (33:31)
  - D.1.2 Multivariable Linear Regression (37:16)
  - D.1.3 Categorical Variables (30:35)
  - D.1.4 General Linear Models (27:48)
- D.2 Generalized Linear Models (Updated February 2020) ...
  - D.2.0 Intro to GLM (9:15)
  - D.2.1 Model Definition (17:42)
  - D.2.2 Exponential Family for GLM (30:13)
  - D.2.3 Model Estimation (39:01)
  - D.2.4 Continuous Response Models (17:35)
  - D.2.5 Binary Response Data (22:52)
  - D.2.6 Non-linear Binary Response Models (Coming Soon) (handout)
  - D.2.7 Poisson Count Models (Coming Soon) (handout)
  - D.2.8 Multinomial Response Models (Coming Soon) (handout)
- D.2. Generalized Linear Models (Old Lessons) ...
  - D.2.1 GLM Overview (8:25)
  - D.2.2 Exponential Families, Redux (23:48)
  - D.2.3 Continuous Response Distributions (15:19)
  - D.2.4 Categorical Response: Binary (18:06)
  - D.2.5 Categorical Response: Multinomial (26:57)
  - D.2.6 Categorical Response: Count Data (13:09)
- D.3 Model Testing and Estimation (Updates Coming February/March 2020) ...
  - D.3.1 Score Statistic (31:11)
  - D.3.2 Wald Statistic (17:15)
  - D.3.3 Likelihood Ratio Statistic: Deviance (20:05)
  - (Old - Watch New D.2.3 instead) D.3.4 Model Estimation (20:29)
  - D.3.5 Testing with the Wald Statistic (44:00)
  - D.3.6 Testing with Deviance (39:49)
  - D.3.7 Testing General Linear Models (38:10)
- D.4 Model Evaluation ...
  - D.4.1 Residuals (19:36)
  - D.4.2 Evaluating Fit Using Residuals (35:59)
  - D.4.3 Goodness of Fit Statistics (23:16)
  - D.4.4 Cross Validation (28:10)
  - D.4.5 Bootstrap (15:00)
- D.5 Model Selection ...
  - D.5.1 Subset Selection (23:22)
  - D.5.2 High-Dimension Models (19:11)
  - D.5.3 Shrinkage Methods (30:18)
  - D.5.4 Dimension Reduction Methods (26:18)
- D.6 Generalized Additive Models ...
  - D.6.1 Generalized Additive Models (17:33)
  - D.6.2 Regression Splines (25:31)
  - D.6.3 Smoothing Splines and Local Regression (21:29)
- D.7 Modeling with R ...
  - D.7.1 Continuous Response (38:56)
  - D.7.2 Categorical Response (28:20)
  - D.7.3 Count Data (25:56)
  - D.7.4 High Dimensional Modeling Part 1 (20:20)
  - D.7.4 High Dimensional Modeling Part 2 (19:54)
  - D.7.5 GAM Part 1 (19:57)
  - D.7.5 GAM Part 2 (16:02)
E. Time Series ... lessons ... min of video
- E.1 Time Series Basics ...
  - E.1.1 Time Series (19:04)
  - E.1.2 Decomposition (16:53)
  - E.1.3 Correlation (27:35)
  - E.1.4 Cross-Correlation (17:14)
- E.2 Time Series Models ...
  - E.2.1 Random Walks (31:47)
  - E.2.2 Autoregressive Models (24:19)
  - E.2.3 Moving Average Models (19:41)
  - E.2.4 ARMA Models (23:15)
  - E.2.5 Non-seasonal ARIMA Models (17:09)
  - E.2.6 Seasonal ARIMA Models (20:06)
- E.3 Time Series Regression ...
  - E.3.1 Regression Modelling (16:13)
  - E.3.2 Seasonal Regression (24:46)
  - E.3.3 Logarithmic and Nonlinear Models (24:46)
What to do after you finish the lessons ... lessons ... min of video
- Managing the work problems study phase ...
  - The Last Lesson (8:33)
Review Lessons ... lessons ... min of video
- Stochastic Processes Review ...
  - Poisson Processes Review (25:28)
  - Continuous/Multiple Lives Review (37:23)
  - Markov Chains Review (21:29)
  - Life Contingencies Review (Coming March 2020) (handout)
  - Simulation (20:59)
- Statistics Review ...
  - Parameter Estimation Review (33:23)
  - Hypothesis Testing Review (42:49)
  - Probability for Insurance Review (35:46)
- General Linear Models Review ...
  - Classical Linear Models Review (42:01)
  - Generalized Linear Models Review (32:06)
  - Model Testing and Estimation Review Part 1 (22:32)
  - Model Testing and Estimation Review Part 2 (25:38)
  - Model Evaluation Review (33:22)
  - Model Selection and Regularization Review (26:46)
  - General Additive Models Review (23:04)
- Time Series Review ...
  - Time Series Basics Review (27:12)
  - Time Series Models Review (31:22)
  - Time Series Regression Review (19:16)

Start Here! ... lessons ... min of video
- How I suggest that you use the Solutions Tab ...
  - Watch Solutions Effectively and Efficiently! (5:49)
B.1 Poisson Processes ... lessons ... min of video
- B.1.1 Exponential Random Variables Part 1 ...
  - B.1.1 #1 (2:28)
  - B.1.1 #2 (3:17)
  - B.1.1 #3 (2:49)
  - B.1.1 #4 (3:11)
  - B.1.1 #5 (1:47)
  - B.1.1 #6 (2:50)
  - B.1.1 #7 (1:08)
- B.1.2 Exponential Random Variables Part 2 ...
  - B.1.2 #1 (1:42)
  - B.1.2 #2 (1:26)
  - B.1.2 #3 (2:15)
  - B.1.2 #4 (7:26)
  - B.1.2 #5 (5:10)
- B.1.3 What is a Poisson Process? ...
  - B.1.3 #1 (2:55)
  - B.1.3 #2 (2:58)
  - B.1.3 #3 (4:31)
  - B.1.3 #4 (5:13)
  - B.1.3 #5 (6:55)
  - B.1.3 #6 (4:47)
  - B.1.3 #7 (1:26)
- B.1.4 Waiting times, Classification ...
  - B.1.4 #1 (2:28)
  - B.1.4 #2 (1:41)
  - B.1.4 #3 (1:34)
  - B.1.4 #4 (1:38)
  - B.1.4 #5 (1:44)
  - B.1.4 #6 (4:14)
  - B.1.4 #7 (1:34)
  - B.1.4 #8 (3:56)
  - B.1.4 #9 (5:08)
  - B.1.4 #10 (2:23)
  - B.1.4 #11 (3:24)
  - B.1.4 #12 (3:38)
  - B.1.4 #13 (6:10)
  - B.1.4 #14 (5:59)
  - B.1.4 #15 (6:49)
  - B.1.4 #16 (3:31)
  - B.1.4 #17 (5:01)
  - B.1.4 #18 (2:37)
  - B.1.4 #19 (3:52)
  - B.1.4 #20 (3:22)
  - B.1.4 #21 (1:36)
  - B.1.4 #22 (4:01)
  - B.1.4 #23 (1:25)
  - B.1.4 #24 (1:52)
  - B.1.4 #25 (4:27)
  - B.1.4 #26 (0:40)
  - B.1.4 #27 (7:41)
  - B.1.4 #28 (1:48)
  - B.1.4 #29 (4:58)
  - B.1.4 #30 (1:45)
  - B.1.4 #31 (1:28)
- B.1.5 Nonhomogeneous Poisson Processes ...
  - B.1.5 #1 (1:10)
  - B.1.5 #2 (3:23)
  - B.1.5 #3 (2:25)
  - B.1.5 #4 (2:36)
  - B.1.5 #5 (2:15)
  - B.1.5 #6 (3:35)
  - B.1.5 #7 (2:32)
  - B.1.5 #8 (3:48)
  - B.1.5 #9 (4:27)
  - B.1.5 #10 (5:04)
  - B.1.5 #11 (1:49)
  - B.1.5 #12 (3:31)
- B.1.6 Compound Poisson Processes ...
  - B.1.6 #1 (1:49)
  - B.1.6 #2 (2:29)
  - B.1.6 #3 (2:36)
  - B.1.6 #4 (5:43)
  - B.1.6 #5 (7:33)
  - B.1.6 #6 (3:35)
  - B.1.6 #7 (4:20)
  - B.1.6 #8 (2:46)
  - B.1.6 #9 (2:24)
  - B.1.6 #10 (2:10)
  - B.1.6 #11 (4:09)
  - B.1.6 #12 (6:44)
  - B.1.6 #13 (4:54)
  - B.1.6 #14 (6:15)
  - B.1.6 #15 (3:58)
  - B.1.6 #16 (2:00)
  - B.1.6 #17 (2:05)
  - B.1.6 #18 (5:45)
  - B.1.6 #19 (4:36)
  - B.1.6 #20 (7:54)
  - B.1.6 #21 (3:47)
  - B.1.6 #22 (2:04)
B.2 Continuous Multiple Lives/Decrements ... lessons ... min of video
- B.2.1 Hazard Rate ...
  - B.2.1 #1 (1:10)
  - B.2.1 #2 (1:25)
  - B.2.1 #3 (3:56)
  - B.2.1 #4 (0:39)
  - B.2.1 #5 (2:37)
  - B.2.1 #6 (2:13)
  - B.2.1 #7 (2:56)
  - B.2.1 #8 (4:59)
  - B.2.1 #9 (4:58)
  - B.2.1 #10 (1:26)
  - B.2.1 #11 (1:50)
  - B.2.1 #12 (4:27)
  - B.2.1 #13 (4:35)
  - B.2.1 #14 (4:09)
  - B.2.1 #15 (3:24)
  - B.2.1 #16 (9:10)
  - B.2.1 #17 (4:34)
  - B.2.1 #18 (2:29)
- B.2.2 Joint-Life Status ...
  - B.2.2 #1 (4:31)
  - B.2.2 #2 (1:56)
  - B.2.2 #3 (4:00)
  - B.2.2 #4 (1:13)
  - B.2.2 #5 (6:14)
  - B.2.2 #6 (6:46)
  - B.2.2 #7 (3:42)
  - B.2.2 #8 (1:49)
  - B.2.2 #9 (3:45)
  - B.2.2 #10 (3:46)
  - B.2.2 #11 (5:35)
- B.2.3 Last-Survivor Status ...
  - B.2.3 #1 (2:07)
  - B.2.3 #2 (1:56)
  - B.2.3 #3 (3:09)
  - B.2.3 #4 (3:00)
  - B.2.3 #5 (4:33)
  - B.2.3 #6 (1:47)
  - B.2.3 #7 (1:06)
  - B.2.3 #8 (5:48)
  - B.2.3 #9 (6:45)
  - B.2.3 #10 (3:48)
  - B.2.3 #11 (3:41)
  - B.2.3 #12 (5:51)
  - B.2.3 #13 (3:55)
- B.2.4 Multiple Decrements ...
  - B.2.4 #1 (1:25)
  - B.2.4 #2 (2:54)
  - B.2.4 #3 (3:12)
  - B.2.4 #4 (4:49)
  - B.2.4 #5 (2:06)
  - B.2.4 #6 (4:29)
  - B.2.4 #7 (3:57)
  - B.2.4 #8 (5:57)
  - B.2.4 #9 (1:40)
  - B.2.4 #10 (2:25)
- B.2.5 Multi-Component Joint-Life and Last-Survivor ...
  - B.2.5 #1 (2:02)
  - B.2.5 #2 (3:14)
  - B.2.5 #3 (0:48)
  - B.2.5 #4 (1:52)
  - B.2.5 #5 (2:29)
  - B.2.5 #6 (3:05)
  - B.2.5 #7 (1:57)
  - B.2.5 #8 (2:12)
  - B.2.5 #9 (1:27)
  - B.2.5 #10 (1:57)
  - B.2.5 #11 (2:50)
- B.2.6 The Bridge System ...
  - B.2.6 #1 (1:58)
  - B.2.6 #2 (1:10)
  - B.2.6 #3 (6:05)
  - B.2.6 #4 (1:45)
  - B.2.6 #5 (3:52)
  - B.2.6 #6 (2:59)
- B.2.7 The k out of n system ...
  - B.2.7 #1 (0:26)
  - B.2.7 #2 (1:40)
  - B.2.7 #3 (4:05)
  - B.2.7 #4 (6:22)
  - B.2.7 #5 (7:19)
- B.2.8 The Random Graph ...
  - B.2.8 #1 (0:43)
  - B.2.8 #2 (1:29)
  - B.2.8 #3 (3:31)
  - B.2.8 #4 (1:05)
  - B.2.8 #5 (1:11)
  - B.2.8 #6 (2:36)
  - B.2.8 #7 (2:53)
  - B.2.8 #8 (2:37)
  - B.2.8 #9 (2:40)
  - B.2.8 #10 (0:45)
- B.2.9 Expected Lifetimes ...
  - B.2.9 #1 (1:30)
  - B.2.9 #2 (2:47)
  - B.2.9 #3 (3:13)
  - B.2.9 #4 (2:30)
  - B.2.9 #5 (2:38)
  - B.2.9 #6 (4:08)
  - B.2.9 #7 (2:49)
  - B.2.9 #8 (8:33)
B.3 Markov Chains ... lessons ... min of video
- B.3.1 Discrete Markov Chains ...
  - B.3.1 #1 (3:54)
  - B.3.1 #2 (3:32)
  - B.3.1 #3 (3:22)
  - B.3.1 #4 (3:13)
  - B.3.1 #5 (2:23)
  - B.3.1 #6 (3:59)
  - B.3.1 #7 (7:18)
  - B.3.1 #8 (4:34)
  - B.3.1 #9 (2:35)
  - B.3.1 #10 (3:11)
  - B.3.1 #11 (4:44)
  - B.3.1 #12 (1:41)
  - B.3.1 #13 (4:48)
  - B.3.1 #14 (2:47)
  - B.3.1 #15 (3:07)
  - B.3.1 #16 (6:14)
  - B.3.1 #17 (7:54)
  - B.3.1 #18 (7:41)
  - B.3.1 #19 (0:57)
  - B.3.1 #20 (7:31)
  - B.3.1 #21 (5:58)
  - B.3.1 #22 (1:55)
- B.3.2 Classification of States ...
  - B.3.2 #1 (1:23)
  - B.3.2 #2 (1:56)
  - B.3.2 #3 (2:55)
  - B.3.2 #4 (2:14)
  - B.3.2 #5 (2:51)
  - B.3.2 #6 (2:16)
  - B.3.2 #7 (3:23)
  - B.3.2 #8 (4:10)
  - B.3.2 #9 (2:24)
  - B.3.2 #10 (2:32)
- B.3.3 Long Run Behavior ...
  - B.3.3 #1 (2:58)
  - B.3.3 #2 (3:30)
  - B.3.3 #3 (5:48)
  - B.3.3 #4 (2:08)
  - B.3.3 #5 (1:50)
  - B.3.3 #6 (4:44)
  - B.3.3 #7 (5:11)
  - B.3.3 #8 (2:11)
  - B.3.3 #9 (5:36)
  - B.3.3 #10 (8:55)
- B.3.4 Applications 1 ...
  - B.3.4 #1 (0:41)
  - B.3.4 #2 (1:43)
  - B.3.4 #3 (1:11)
  - B.3.4 #4 (1:37)
  - B.3.4 #5 (1:32)
  - B.3.4 #6 (3:05)
  - B.3.4 #7 (7:20)
  - B.3.4 #8 (6:28)
  - B.3.4 #9 (2:08)
  - B.3.4 #10 (2:21)
- B.3.5 Applications 2: Branching Processes ...
  - B.3.5 #1 (1:27)
  - B.3.5 #2 (1:38)
  - B.3.5 #3 (1:30)
  - B.3.5 #4 (4:37)
  - B.3.5 #5 (1:52)
  - B.3.5 #6 (3:10)
  - B.3.5 #7 (1:17)
  - B.3.5 #8 (3:55)
  - B.3.5 #9 (9:00)
  - B.3.5 #10 (0:41)
B.4 Life Contingencies 0 lessons 0 min of video
B.5 Simulation 0 lessons 0 min of video
C.1 Parameter Estimation ... lessons ... min of video
- C.1.1 Estimator Basics ...
  - C.1.1 #1 (3:56)
  - C.1.1 #2 (3:14)
- C.1.2 Comparing Estimators: Mean and Variance ...
  - C.1.2 #1 (0:50)
  - C.1.2 #2 (1:37)
  - C.1.2 #3 (2:59)
  - C.1.2 #4 (1:12)
  - C.1.2 #5 (2:25)
  - C.1.2 #6 (1:23)
  - C.1.2 #7 (2:37)
  - C.1.2 #8 (2:42)
  - C.1.2 #9 (4:38)
  - C.1.2 #10 (1:31)
  - C.1.2 #11 (1:03)
  - C.1.2 #12 (8:03)
  - C.1.2 #13 (2:07)
  - C.1.2 #14 (1:17)
  - C.1.2 #15 (0:48)
- C.1.3 Comparing Estimators: Likelihood and Sufficiency ...
  - C.1.3 #1 (3:59)
  - C.1.3 #2 (2:13)
  - C.1.3 #3 (1:02)
  - C.1.3 #4 (2:27)
  - C.1.3 #5 (5:10)
  - C.1.3 #6 (4:40)
  - C.1.3 #7 (1:30)
  - C.1.3 #8 (0:50)
- C.1.4 The Maximum Likelihood Estimator ...
  - C.1.4 #1 (2:37)
  - C.1.4 #2 (0:48)
  - C.1.4 #3 (2:21)
  - C.1.4 #4 (1:51)
  - C.1.4 #5 (2:36)
  - C.1.4 #6 (2:20)
  - C.1.4 #7 (4:35)
  - C.1.4 #8 (4:23)
  - C.1.4 #9 (3:16)
  - C.1.4 #10 (3:21)
  - C.1.4 #11 (1:02)
  - C.1.4 #12 (3:05)
  - C.1.4 #13 (1:23)
  - C.1.4 #14 (2:04)
  - C.1.4 #15 (1:50)
  - C.1.4 #16 (3:53)
  - C.1.4 #17 (3:38)
  - C.1.4 #18 (2:10)
  - C.1.4 #19 (2:22)
  - C.1.4 #20 (5:12)
  - C.1.4 #21 (6:54)
  - C.1.4 #22 (2:26)
  - C.1.4 #23 (3:32)
  - C.1.4 #24 (1:55)
  - C.1.4 #25 (2:53)
  - C.1.4 #26 (7:11)
  - C.1.4 #27 (2:28)
- C.1.5 Advanced Likelihood Functions ...
  - C.1.5 #1 (6:49)
  - C.1.5 #2 (5:28)
  - C.1.5 #3 (1:32)
  - C.1.5 #4 (1:39)
  - C.1.5 #5 (2:17)
  - C.1.5 #6 (1:53)
  - C.1.5 #7 (4:16)
  - C.1.5 #8 (1:16)
  - C.1.5 #9 (1:53)
  - C.1.5 #10 (3:28)
  - C.1.5 #11 (3:03)
  - C.1.5 #12 (4:47)
  - C.1.5 #13 (2:40)
  - C.1.5 #14 (5:00)
  - C.1.5 #15 (3:21)
  - C.1.5 #16 (2:31)
- C.1.6 Variance of MLE ...
  - C.1.6 #1 (2:12)
  - C.1.6 #2 (1:51)
  - C.1.6 #3 (4:36)
  - C.1.6 #4 (0:43)
  - C.1.6 #5 (2:36)
  - C.1.6 #6 (5:54)
  - C.1.6 #7 (4:13)
  - C.1.6 #8 (3:10)
  - C.1.6 #9 (5:01)
  - C.1.6 #10 (4:12)
- C.1.7 Exponential Family ...
  - C.1.7 #1 (2:54)
  - C.1.7 #2 (3:03)
  - C.1.7 #3 (2:13)
  - C.1.7 #4 (2:34)
  - C.1.7 #5 (3:11)
  - C.1.7 #6 (2:19)
  - C.1.7 #7 (5:57)
  - C.1.7 #8 (1:22)
  - C.1.7 #9 (2:22)
  - C.1.7 #10 (3:56)
  - C.1.7 #11 (2:05)
  - C.1.7 #12 (3:03)
  - C.1.7 #13 (1:30)
  - C.1.7 #14 (1:39)
  - C.1.7 #15 (3:54)
C.2 Hypothesis Testing ... lessons ... min of video
- C.2.1 Hypothesis Testing ...
  - C.2.1 #1 (3:45)
  - C.2.1 #2 (7:03)
  - C.2.1 #3 (1:39)
  - C.2.1 #4 (2:19)
  - C.2.1 #5 (2:34)
  - C.2.1 #6 (4:10)
  - C.2.1 #7 (2:44)
- C.2.2 Tests for the mean: ``Known'' variance ...
  - C.2.2 #1 (1:50)
  - C.2.2 #2 (2:28)
  - C.2.2 #3 (4:12)
  - C.2.2 #4 (2:51)
  - C.2.2 #5 (7:22)
  - C.2.2 #6 (6:28)
  - C.2.2 #7 (7:18)
  - C.2.2 #8 (4:51)
  - C.2.2 #9 (2:09)
  - C.2.2 #10 (1:43)
  - C.2.2 #11 (0:50)
  - C.2.2 #12 (1:14)
  - C.2.2 #13 (0:58)
  - C.2.2 #14 (2:06)
  - C.2.2 #15 (3:43)
  - C.2.2 #16 (11:15)
  - C.2.2 #17 (3:55)
  - C.2.2 #18 (4:07)
  - C.2.2 #19 (4:44)
  - C.2.2 #20 (4:24)
- C.2.3 Tests for the mean: ``Unknown'' Variance ...
  - C.2.3 #1 (2:10)
  - C.2.3 #2 (3:18)
  - C.2.3 #3 (2:42)
  - C.2.3 #4 (2:01)
  - C.2.3 #5 (2:36)
  - C.2.3 #6 (1:29)
  - C.2.3 #7 (3:08)
  - C.2.3 #8 (1:51)
  - C.2.3 #9 (2:54)
  - C.2.3 #10 (2:20)
  - C.2.3 #11 (4:17)
- C.2.4 Comparing Populations ...
  - C.2.4 #1 (2:59)
  - C.2.4 #2 (3:03)
  - C.2.4 #3 (0:59)
  - C.2.4 #4 (4:37)
  - C.2.4 #5 (3:04)
  - C.2.4 #6 (2:00)
  - C.2.4 #7 (2:45)
  - C.2.4 #8 (2:32)
  - C.2.4 #9 (5:02)
  - C.2.4 #10 (3:43)
  - C.2.4 #11 (4:33)
  - C.2.4 #12 (3:53)
  - C.2.4 #13 (5:41)
  - C.2.4 #14 (3:09)
- C.2.5 Tests for Variance ...
  - C.2.5 #5 (2:55)
  - C.2.5 #2 (2:59)
  - C.2.5 #3 (2:08)
  - C.2.5 #4 (3:34)
  - C.2.5 #5 (3:19)
  - C.2.5 #6 (1:51)
  - C.2.5 #7 (0:52)
  - C.2.5 #8 (1:15)
  - C.2.5 #9 (1:20)
  - C.2.5 #10 (1:59)
  - C.2.5 #11 (2:32)
  - C.2.5 #12 (1:13)
- C.2.6 Confidence Intervals ...
  - C.2.6 #1 (1:41)
  - C.2.6 #2 (2:14)
  - C.2.6 #3 (1:52)
  - C.2.6 #4 (1:38)
  - C.2.6 #5 (1:31)
  - C.2.6 #6 (2:46)
  - C.2.6 #7 (5:24)
  - C.2.6 #8 (2:05)
  - C.2.6 #9 (1:55)
  - C.2.6 #10 (3:03)
  - C.2.6 #11 (6:17)
  - C.2.6 #12 (7:25)
  - C.2.6 #13 (4:40)
- C.2.7 Other Chi-Square Tests ...
  - C.2.7 #1 (0:27)
  - C.2.7 #2 (1:36)
  - C.2.7 #3 (2:11)
  - C.2.7 #4 (0:59)
  - C.2.7 #5 (1:29)
  - C.2.7 #6 (5:28)
  - C.2.7 #7 (3:33)
  - C.2.7 #8 (4:02)
  - C.2.7 #9 (1:00)
  - C.2.7 #10 (2:41)
  - C.2.7 #11 (3:31)
  - C.2.7 #12 (5:13)
  - C.2.7 #13 (3:40)
  - C.2.7 #14 (6:18)
  - C.2.7 #15 (2:30)
- C.2.8 Likelihood Ratio Test ...
  - C.2.8 #1 (2:37)
  - C.2.8 #2 (2:57)
  - C.2.8 #3 (4:25)
  - C.2.8 #4 (4:42)
  - C.2.8 #5 (8:53)
  - C.2.8 #6 (8:20)
  - C.2.8 #7 (4:04)
  - C.2.8 #8 (6:59)
  - C.2.8 #9 (4:57)
  - C.2.8 #10 (4:31)
  - C.2.8 #11 (2:47)
  - C.2.8 #12 (6:07)
  - C.2.8 #13 (2:52)
  - C.2.8 #14 (2:16)
  - C.2.8 #15 (6:50)
  - C.2.8 #16 (11:38)
- C.2.9 Kolmogorov-Smirnov Test ...
  - C.2.9 #1 (3:29)
  - C.2.9 #2 (0:50)
  - C.2.9 #3 (3:25)
  - C.2.9 #4 (3:26)
  - C.2.9 #5 (3:09)
  - C.2.9 #6 (4:16)
C.3 Order Statistics ... lessons ... min of video
- C.3.1 Order Statistics ...
  - C.3.1 #1 (1:18)
  - C.3.1 #2 (2:16)
  - C.3.1 #3 (3:06)
  - C.3.1 #4 (1:29)
  - C.3.1 #5 (3:28)
  - C.3.1 #6 (2:21)
  - C.3.1 #7 (3:23)
  - C.3.1 #8 (4:52)
  - C.3.1 #9 (1:53)
  - C.3.1 #10 (1:32)
  - C.3.1 #11 (1:58)
  - C.3.1 #12 (3:23)
- C.3.2 Uniform and Exponential Order Stats ...
  - C.3.2 #1 (2:27)
  - C.3.2 #2 (2:18)
  - C.3.2 #3 (2:39)
  - C.3.2 #4 (13:20)
  - C.3.2 #5 (2:46)
  - C.3.2 #6 (7:51)
  - C.3.2 #7 (4:01)
  - C.3.2 #8 (4:50)
  - C.3.2 #9 (9:15)
  - C.3.2 #10 (0:59)
  - C.3.2 #11 (2:12)
  - C.3.2 #12 (0:47)
  - C.3.2 #13 (9:20)
  - C.3.2 #14 (3:27)
  - C.3.2 #15 (5:45)
  - C.3.2 #16 (1:45)
  - C.3.2 #17 (4:43)
  - C.3.2 #18 (3:16)
  - C.3.2 #19 (2:02)
  - C.3.2 #20 (4:14)
  - C.3.2 #21 (2:28)
  - C.3.2 #22 (2:29)
  - C.3.2 #23 (2:29)
  - C.3.2 #24 (1:59)
  - C.3.2 #25 (2:06)
  - C.3.2 #26 (1:58)
D.1 Classical Linear Models ... lessons ... min of video
- D.1.1 Single Variable Linear Regression ...
  - D.1.1 #1 (1:51)
  - D.1.1 #2 (2:14)
  - D.1.1 #3 (1:27)
  - D.1.1 #4 (2:37)
- D.1.2 Multivariable Linear Regression ...
  - D.1.2 #1 (1:50)
  - D.1.2 #2 (2:36)
  - D.1.2 #3 (5:59)
- D.1.3 Categorical Variables ...
  - D.1.3 #1 (1:47)
  - D.1.3 #2 (0:47)
  - D.1.3 #3 (0:51)
- D.1.4 General Linear Models ...
  - D.1.4 #1 (0:55)
  - D.1.4 #2 (1:46)
  - D.1.4 #3 (1:37)
  - D.1.4 #4 (1:54)
  - D.1.4 #5 (2:57)
  - D.1.4 #6 (3:25)
  - D.1.4 #7 (6:18)
  - D.1.4 #8 (6:03)
  - D.1.4 #9 (1:28)
  - D.1.4 #10 (1:04)
D.2 Generalized Linear Models ... lessons ... min of video
- D.2.2 Exponential Families, Redux ...
  - D.2.2 #1 (2:22)
  - D.2.2 #2 (3:17)
  - D.2.2 #3 (2:37)
  - D.2.2 #4 (2:18)
  - D.2.2 #5 (1:50)
  - D.2.2 #6 (3:53)
  - D.2.2 #7 (5:35)
  - D.2.2 #8 (4:25)
  - D.2.2 #9 (3:04)
  - D.2.2 #10 (3:24)
  - D.2.2 #11 (1:40)
  - D.2.2 #12 (2:08)
  - D.2.2 #13 (3:58)
  - D.2.2 #14 (2:22)
  - D.2.2 #15 (2:04)
  - D.2.2 #16 (2:35)
- D.2.3 Continuous Response Distributions ...
  - D.2.3 #1 (1:17)
  - D.2.3 #2 (2:49)
  - D.2.3 #3 (2:23)
  - D.2.3 #4 (2:24)
  - D.2.3 #5 (2:00)
  - D.2.3 #6 (1:47)
  - D.2.3 #7 (4:04)
  - D.2.3 #8 Exam S Spring 2017 #29 (1:37)
  - D.2.3 #9 Exam S Fall 2016 #32 (1:13)
  - D.2.3 #10 Exam S Fall 2017 #31 (1:05)
  - D.2.3 #11 Exam S Fall 2017 #32 (0:44)
  - D.2.3 #12 (1:32)
  - D.2.3 #13 (2:23)
  - D.2.3 #14 (2:15)
- D.2.4 Categorical Response: Binary ...
  - D.2.4 #1 (2:37)
  - D.2.4 #2 (2:05)
  - D.2.4 #3 (2:38)
  - D.2.4 #4 (2:54)
  - D.2.4 #5 (4:33)
- D.2.5 Categorical Response: Multinomial ...
  - D.2.5 #1 (3:18)
  - D.2.5 #2 (2:47)
- D.2.6 Categorical Response: Count Data ...
  - D.2.6 #1 (0:47)
  - D.2.6 #2 (2:09)
  - D.2.6 #3 (1:44)
  - D.2.6 #4 (1:24)
  - D.2.6 #5 (3:24)
  - D.2.6 #6 (2:11)
D.3 Model Testing and Estimation ... lessons ... min of video
- D.3.1 Score Statistic ...
  - D.3.1 #1 (1:56)
  - D.3.1 #2 (1:55)
  - D.3.1 #3 (2:47)
  - D.3.1 #4 (1:46)
  - D.3.1 #5 (3:39)
  - D.3.1 #6 (2:21)
- D.3.2 Wald Statistic ...
  - D.3.2 #1 (1:36)
  - D.3.2 #2 (2:13)
- D.3.3 Likelihood Ratio Statistic: Deviance ...
  - D.3.3 #1 (1:57)
  - D.3.3 #2 (0:52)
  - D.3.3 #3 (4:48)
  - D.3.3 #4 (3:26)
- D.3.4 Model Estimation ...
  - D.3.4 #1 (1:58)
  - D.3.4 #2 (1:52)
  - D.3.4 #3 (1:42)
  - D.3.4 #4 (2:35)
  - D.3.4 #5 (5:38)
  - D.3.4 #6 (5:26)
  - D.3.4 #7 (4:51)
- D.3.5 Testing with the Wald Statistic ...
  - D.3.5 #1 (3:44)
  - D.3.5 #2 (2:29)
  - D.3.5 #3 (6:35)
  - D.3.5 #4 (1:18)
  - D.3.5 #5 (2:26)
  - D.3.5 #6 (3:06)
  - D.3.5 #7 (2:23)
  - D.3.5 #8 (3:22)
  - D.3.5 #9 (0:49)
- D.3.6 Testing with Deviance ...
  - D.3.6 #1 (1:02)
  - D.3.6 #2 (2:12)
  - D.3.6 #3 (2:33)
  - D.3.6 #4 (3:21)
  - D.3.6 #5 (2:33)
  - D.3.6 #6 (3:16)
  - D.3.6 #7 (2:07)
- D.3.7 Testing General Linear Models ...
  - D.3.7 #1 (7:51)
  - D.3.7 #2 (6:26)
  - D.3.7 #3 (4:24)
  - D.3.7 #4 (4:08)
  - D.3.7 #5 (3:41)
  - D.3.7 #6 (7:44)
  - D.3.7 #7 (5:46)
  - D.3.7 #8 (4:36)
  - D.3.7 #9 (4:36)
  - D.3.7 #10 (6:32)
  - D.3.7 #11 (8:04)
  - D.3.7 #12 (4:20)
  - D.3.7 #13 (6:09)
  - D.3.7 #14 (3:40)
D.4 Model Evaluation ... lessons ... min of video
- D.4.1 Residuals ...
  - D.4.1 #4 (1:30)
- D.4.2 Evaluating Fit Using Residuals ...
  - D.4.2 #1 (1:22)
  - D.4.2 #3 (2:05)
- D.4.3 Goodness of Fit Statistics ...
  - D.4.3 #1 (2:04)
  - D.4.3 #3 (0:35)
  - D.4.3 #5 (2:10)
  - D.4.3 #6 (2:20)
  - D.4.3 #7 (2:56)
D.5 Model Selection and Regularization ... lessons ... min of video
- D.5.1 Subset Selection ...
  - D.5.1 #1 (0:20)
  - D.5.1 #5 (2:25)
  - D.5.1 #7 (0:25)
  - D.5.1 #9 (0:20)
- D.5.2 High-Dimensional Models ...
  - D.5.2 #1 (1:13)
  - D.5.2 #2 (1:25)
D.6 Generalized Additive Models 0 lessons 0 min of video
D.7 Modeling with R ... lessons ... min of video
- D.7.1 Continuous Response ...
  - D.7.1 #1 (1:27)
  - D.7.1 #2 (1:53)
  - D.7.1 #3 (0:36)
- D.7.2 Categorical Response ...
  - D.7.2 #1 (2:52)
  - D.7.2 #2 (2:03)
  - D.7.2 #3 (2:06)
  - D.7.2 #4 (2:51)
- D.7.3 Count Data ...
  - D.7.3 #1 (2:06)
E.1 Time Series Basics ... lessons ... min of video
- E.1.1 Time Series ...
  - E.1.1 #1 (0:18)
  - E.1.1 #2 (1:22)
- E.1.2 Decomposition ...
  - E.1.2. #1 (2:45)
  - E.1.2 #2 (3:43)
  - E.1.2 #3 (3:55)
  - E.1.2 #4 (2:44)
  - E.1.2 #5 (3:08)
  - E.1.2 #6 (3:30)
  - E.1.2 #7 (5:30)
  - E.1.2 #8 (2:43)
  - E.1.2 #9 (6:54)
  - E.1.2 #10 (4:59)
- E.1.3 Correlation ...
  - E.1.3 #1 (0:50)
  - E.1.3 #2 (3:57)
  - E.1.3 #3 (2:52)
  - E.1.3 #4 (4:28)
  - E.1.3 #5 (1:57)
- E.1.4 Cross-Correlation ...
  - E.1.4 #1 (1:38)
  - E.1.4 #2 (2:39)
  - E.1.4 #3 (2:23)
  - E.1.4 #4 (4:44)
  - E.1.4 #5 (2:05)
E.2 Time Series Models ... lessons ... min of video
- E.2.1 Random Walks ...
  - E.2.1 #1 (1:01)
  - E.2.1 #2 (1:58)
  - E.2.1 #3 (0:47)
  - E.2.1 #4 (2:28)
  - E.2.1 #6 (1:37)
  - E.2.1 #7 (10:17)
- E.2.2 Autoregressive Models ...
  - E.2.2 #1 (4:06)
  - E.2.2 #2 (5:50)
  - E.2.2 #3 (3:41)
  - E.2.2 #4 (2:15)
  - E.2.2 #5 (0:16)
  - E.2.2 #6 (1:04)
  - E.2.2 #7 (1:19)
  - E.2.2 #8 (5:19)
  - E.2.2 #9 (1:31)
  - E.2.2 #10 (1:40)
  - E.2.2 #11 (3:16)
  - E.2.2 #12 (2:31)
  - E.2.2 #13 (1:50)
  - E.2.2 #14 (4:53)
- E.2.3 Moving Average Models ...
  - E.2.3 #1 (2:09)
  - E.2.3 #2 (2:58)
  - E.2.3 #3 (3:44)
  - E.2.3 #4 (0:45)
  - E.2.3 #5 (1:20)
  - E.2.3 #6 (2:31)
  - E.2.3 #7 (1:37)
  - E.2.3 #8 (4:24)
  - E.2.3 #9 (5:26)
  - E.2.3 #10 (0:39)
  - E.2.3 #11 (11:49)
  - E.2.3 #12 (3:42)
  - E.2.3 #13 (4:11)
  - E.2.3 #14 (4:26)
- E.2.4 ARMA Models ...
  - E.2.4 #1 (0:41)
  - E.2.4 #2 (1:48)
  - E.2.4 #3 (3:40)
  - E.2.4 #4 (1:42)
  - E.2.4 #5 (3:15)
  - E.2.4 #6 (2:29)
  - E.2.4 #7 (1:51)
  - E.2.4 #8 (2:06)
  - E.2.4 #9 (2:16)
  - E.2.4 #10 (1:41)
  - E.2.4 #11 (1:42)
  - E.2.4 #12 (4:27)
  - E.2.4 #13 (4:57)
  - E.2.4#14 (3:24)
- E.2.5 Non-seasonal ARIMA Models ...
  - E.2.5 #1 (5:30)
  - E.2.5 #2 (3:23)
  - E.2.5 #3 (4:05)
  - E.2.5 #4 (1:48)
  - E.2.5 #5 (3:43)
  - E.2.5 #6 (4:01)
- E.2.6 Seasonal ARIMA Models ...
  - E.2.6 #1 (3:59)
  - E.2.6 #2 (1:49)
  - E.2.6 #3 (2:45)
  - E.2.6 #5 (3:42)
  - E.2.6 #6 (4:48)
E.3 Time Series Regression ... lessons ... min of video
- E.3.1 Regression Modelling ...
  - E.3.1 #1 (1:31)
  - E.3.1 #2 (1:04)
- E.3.2 Seasonal Regression ...
  - E.3.2 #1 (1:27)
  - E.3.2 #2 (2:29)
- E.3.3 Logarithmic and Nonlinear Models ...
  - E.3.3 #1 (1:37)
  - E.3.3 #2 (1:18)

Watch Me First! ... lessons ... min of video
- Sample Exams Strategy ...
  - Sample Exam Strategy (19:54)
- Sample Exams Scheduling (Update coming in March for the April 2020 sitting) ...
  - Sample Exam Scheduling (4:50)
Sample Exam 1 (Updated Fall 2019) ... lessons ... min of video
- Questions ...
  - Questions PDF (handout)
  - Answer Key PDF (handout)
  - Solutions PDF (handout)
  - Lesson Map (handout)
- Video Solutions ...
  - Sample exam 1 Problem #1 (2:34)
  - Sample exam 1 Problem #2 (3:17)
  - Sample exam 1 Problem #3 (2:46)
  - Sample exam 1 Problem #4 (2:30)
  - Sample exam 1 Problem #5 (3:51)
  - Sample exam 1 Problem #6 (3:39)
  - Sample exam 1 Problem #7 (3:00)
  - Sample exam 1 Problem #8 (1:04)
  - Sample exam 1 Problem #9 (3:09)
  - Sample exam 1 Problem #10 (3:14)
  - Sample exam 1 Problem #11 (5:27)
  - Sample exam 1 Problem #12 (2:52)
  - Sample exam 1 Problem #14 (3:05)
  - Sample exam 1 Problem #13 (2:52)
  - Sample exam 1 Problem #15 (2:17)
  - Sample exam 1 Problem #16 (5:12)
  - Sample exam 1 Problem #17 (5:21)
  - Sample exam 1 Problem #18 (2:57)
  - Sample exam 1 Problem #19 (3:11)
  - Sample exam 1 Problem #20 (4:36)
  - Sample exam 1 Problem #21 (2:49)
  - Sample exam 1 Problem #22 (1:30)
  - Sample exam 1 Problem #23 (2:12)
  - Sample exam 1 Problem #24 (3:19)
  - Sample exam 1 Problem #25 (2:27)
  - Sample exam 1 Problem #26 (3:13)
  - Sample exam 1 Problem #27 (2:59)
  - Sample exam 1 Problem #28 (2:33)
  - Sample exam 1 Problem #29 (2:23)
  - Sample exam 1 Problem #30 (3:50)
  - Sample exam 1 Problem #31 (2:35)
  - Sample exam 1 Problem #32 (2:31)
  - Sample exam 1 Problem #33 (2:49)
  - Sample exam 1 Problem #34 (2:09)
  - Sample exam 1 Problem #35 (1:28)
  - Sample exam 1 Problem #36 (4:40)
  - Sample exam 1 Problem #37 (3:25)
  - Sample exam 1 Problem #38 (3:12)
  - Sample exam 1 Problem #39 (4:02)
  - Sample exam 1 Problem #40 (1:39)
  - Sample exam 1 Problem #41 (1:58)
  - Sample exam 1 Problem #42 (4:13)
  - Sample exam 1 Problem #43 (3:32)
  - Sample exam 1 Problem #44 (0:39)
  - Sample exam 1 Problem #45 (3:37)
Spring 2018 MAS-I ... lessons ... min of video
- Questions ...
  - Spring 2018 MAS-I pdf (handout)
  - Answer Key and Handwritten Solutions (handout)
  - Lesson Map (handout)
- Video Solutions ...
  - Sp 2018 MAS-I #1 (1:22)
  - Sp 2018 MAS-I #2 (1:41)
  - Sp 2018 MAS-I #3 (2:35)
  - Sp 2018 MAS-I #4 (2:16)
  - Sp 2018 MAS-I #5 (1:32)
  - Sp 2018 MAS-I #6 (4:23)
  - Sp 2018 MAS-I #7 (1:18)
  - Sp 2018 MAS-I #8 (1:38)
  - Sp 2018 MAS-I #9 (2:11)
  - Sp 2018 MAS-I #10 (2:58)
  - Sp 2018 MAS-I #11 (2:42)
  - Sp 2018 MAS-I #12 (1:54)
  - Sp 2018 MAS-I #13 (3:40)
  - Sp 2018 MAS-I #14 (3:34)
  - Sp 2018 MAS-I #15 (2:31)
  - Sp 2018 MAS-I #16 (2:27)
  - Sp 2018 MAS-I #17 (4:43)
  - Sp 2018 MAS-I #18 (3:32)
  - Sp 2018 MAS-I #19 (2:02)
  - Sp 2018 MAS-I #20 (4:14)
  - Sp 2018 MAS-I #21 (3:00)
  - Sp 2018 MAS-I #22 (4:51)
  - Sp 2018 MAS-I #23 (1:15)
  - Sp 2018 MAS-I #24 (3:08)
  - Sp 2018 MAS-I #25 (2:50)
  - Sp 2018 MAS-I #26 (2:43)
  - Sp 2018 MAS-I #27 (1:16)
  - Sp 2018 MAS-I #28 (2:45)
  - Sp 2018 MAS-I #29 (1:06)
  - Sp 2018 MAS-I #30 (3:25)
  - Sp 2018 MAS-I #31 (3:26)
  - Sp 2018 MAS-I #32 (3:07)

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Exam MAS-I