Explain Type I/II errors vs precision/recall

Questions

1. Define Type I error and Type II error in hypothesis testing, and map them to false positives and false negatives .
2. Explain how Type I/II errors relate (or don’t directly relate) to precision and recall in binary classification.
3. Give concrete examples of when Type I error is worse vs when Type II error is worse .
4. Given a scenario (e.g., medical test, fraud detection, spam filter, moderation), identify which outcome is Type I vs Type II and which metric you would prioritize.