Explainers

AI-generated introductions to topics in statistics, machine learning, and product discovery.

1. One Armed Bandit Problem
   Exploration vs. exploitation trade-off in sequential decision making, strategies, and real-world applications.
2. P-Values & Statistical Significance
   Hypothesis testing, p-values, significance levels, Type I/II errors, p-hacking, and common misinterpretations in statistics.
3. A/B Testing
   Comparing two versions with statistical significance, sample size calculation, common pitfalls, and when to test.
4. Random Decision Trees & Forests
   Ensemble learning combining multiple trees via bootstrapping and random features. Advantages, hyperparameters, and variants like Extra Trees and Gradient Boosting.
5. Opportunity Solution Tree Example
   A filled in opportunity solution tree for a video streaming app, from outcome down to assumption tests, as a companion to the Product Talk article.