Hi all! 👋
In this repository, I collect drafts and published Jupyter Notebooks for blog posts on my website and Medium. I write to learn and help others.
If you find mistakes or you have suggestions for new posts, let me know! Hug 🤗
-
An in-depth guide to the state-of-the-art variance reduction technique for A/B tests
-
How to Compare Two or More Distributions
A complete guide to comparing distributions, from visualization to statistical tests
-
Understanding Contamination Bias
Problems and solutions of linear regression with multiple mutually exclusive treatments
-
Double Debiased Machine Learning (part 2)
How to remove regularization bias using post-double selection
-
Double Debiased Machine Learning (part 1)
Causal inference, machine learning, and regularization bias
-
Understanding Omitted Variable Bias
A step-by-step guide to the most pervasive type of bias
-
Understanding The Frisch-Waugh-Lovell Theorem
A step-by-step guide to one of the most powerful theorems in causal inference
-
Goodbye Scatterplot, Welcome Binned Scatterplot
How to visualize and do inference on conditional means
-
Experiments, Peeking, and Optimal Stopping
How to run valid experiments with smaller sample sizes with the Sequential Probability Ratio Test
-
How to select control variables for causal inference using Directed Acyclic Graphs
