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Lessons

  • Lesson 0: Setting up computing resources
  • Lesson 1: Polars and split-apply-combine
  • Lesson 2: Exploratory plotting
  • Lesson 3: Probability distributions and the plug-in principle
  • Lesson 4: Nonparametric inference with hacker stats
  • Lesson 5: Generative modeling and parametric inference
  • Lesson 6: Maximum likelihood estimation
  • Lesson 7: Variate-covariate modeling
  • Lesson 8: Model assessment

Exercises

  • Exercise 1. Polars and split-apply-combine
  • Exercise 2. Exploratory plotting
  • Exercise 3. Working with probability distributions
  • Exercise 4: Nonparametric hacker stats
  • Exercise 5: Generative modeling
  • Exercise 6: Maximum likelihood estimation
  • Exercise 7: MLE with variate-covariate models
  • Exercise 8: Model assessment

Schedule

  • Schedule overview
  • Daily schedule
PoL workshop on statistical inference, part 1
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Last updated on Aug 22, 2024.

© 2021–2024 Justin Bois. With the exception of pasted graphics, where the source is noted, this work is licensed under a Creative Commons Attribution License CC-BY 4.0. All code contained herein is licensed under an MIT license.


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