Week 4

Overview

Caution📚 HW2 (Deadline 11:59pm Mon Feb 2)

Github Classroom Assignment

Learning Goals

• Understand the mechanics of the sampling distribution
• Understand what statistical inference means in practice
• Understand the “4 Horseman” of resampling:
  • Monte-Carlo simulation (assumptions)
  • Bootstrap (resampling with replacement)
  • Permutation (shuffling)
  • Cross-validation (generalization)

Slides

TipSlides Wed Jan 26

Materials

Caution📚 Lab

Github Classroom Assignment

Mentioned References

• Statistics for Hackers
  • Download
  • Youtube

Additional References

Modeling & Inference

• Central Limit Theorem
• Overview of basic statistical models
• Overview of basic statistical inference
• What is sampling?
• Statistical Inference & Hypothesis testing
• Statistical Inference enables Bad Science. Statistical Thinking Enables Good Science

Resampling Approaches

• Hypothesis testing with randomization (Permutation)
• Confidence intervals with Bootstrapping
• Bootstrapping a single mean
• The Importance of Data Splitting
• Cross Validation
• Permutation test