Mathematical Statistics

Math 392 | Reed College | Spring 2020

Schedule

Week 13: Markoc Chain Monte Carlo, cont.

Monday

• Join class
• Rejection Sampling and Buffon's Needle

Wednesday

• Join class
• Course in Review
• Office hours 3 - 5 pm PST

Friday

• Join class
• Guest Lecture: Hidden Markov Models with Gibbs Sampling
• Office hours 3 - 5 pm PST

Week 12: Bayesian Modeling

Monday

• Join class
• Review
  • PS 8 and the AR-1 Model
  • Inference on lm() and glm()

Wednesday

• Join class
• Gibbs Sampling
• Office hours 3 - 5 pm PST

Friday

• Join class
• Metropolis Algorithm
• Office hours 3 - 5 pm PST

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Week 11: Generalized Linear Models / Inference on MLEs

Monday

• Join class
• Multivariate Normal

Wednesday

• Join class
• Generalized Linear Models
• Logistic Regression
• Office hours 3 - 5 pm PST

Friday

• Join class
• Inference for the MLE
• Office hours 3 - 5 pm PST

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Week 10: Multiple Linear Regression

Monday

• Join class
• Matrix Form of Regression

Wednesday

• Join class
• The Hat Matrix and Ridge Regression
• Office hours 3 - 5 pm PST

Friday

• Join class
• The Gauss-Markov Theorem
  • Video 1
  • Video 2
  • Video 3
• Office hours 3 - 5 pm PST

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Week 9: Simple Linear Regression

Monday

• Join class
• Parameters of Joint Distributions
• Method of Least Squares
• Reading: p. 689 - 697

Wednesday

• Join class
• Simple Linear Regression Model
• Reading: p. 698 - 706
• Office hours 3 - 5 pm PST

Friday

• Join class
• Inference for Regression
• Reading: p. 707 - 720
• Problem Set 7 due Monday 8 pm on Gradescope
• Office hours 3 - 5 pm PST

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Week 7/8: Hypothesis Tests

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Week 6: Frequentist, Bayesian, and Bootstrap CI

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Week 5: Bootstrap Sampling Distributions

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Week 4: Sampling Distributions of Estimators

Monday

• Chi-squared Distribution
• Reading: p. 464 - 472

Wednesday

• t Distribution
• Reading: p. 480 - 484

Friday

• Confidence Intervals
• Reading: p. 485 - 493
• Problem Set 4 due at 10 pm in the box outside my door

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Week 3: Alternative Frameworks: Likelihood and Method of Moments

Monday

• Likelihood Theory
• Reading: p. 417 - 425

Wednesday

• Consistency and Bias
• Reading: p. 426 - 430

Friday

• Method of Moments
• Reading: p. 430 - 434
• Problem Set 3 due at 10 pm in the box outside my door

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Week 2: The Mechanics of Bayesian Inference

Monday

• Conjugate Priors
• Reading: p. 394 - 405
• Please finish Normal-Normal example before next class

Wednesday

• Bayes Estimators
• Reading: p. 408 - 416

Friday

• Evaluating Bayes estimators
• Problem Set 2 due at 10 pm in the box outside my door

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Week 1: Intro

Monday

• Statistical Inference
• Reading: p. 376-384
• Please join the slack group.
  • Reply to my post requesting snippets of tex and r code for use in PS1.
• PS1 due Friday in class

Wednesday

• No class

Friday

• Priors and Posteriors
• Reading: p. 385 - 393