Lessons

Lesson 0: Configuring your computer
Lesson 1: Pandas 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. Pandas 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

»
Lesson 4: Nonparametric inference with hacker stats
View page source

Lesson 4: Nonparametric inference with hacker stats

Confidence intervals
Performing bootstrap calculations
Pairs bootstrap and correlation
Confidence interval of an ECDF

Previous Next

Last updated on Jul 07, 2022.

© 2021 Justin Bois and BE/Bi 103 a course staff. 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.

This document was prepared at Caltech with financial support from the Donna and Benjamin M. Rosen Bioengineering Center.

Built with Sphinx using a theme provided by Read the Docs.