Explain Type I vs Type II errors
Company: OneMain Financial
Role: Data Scientist
Category: Statistics & Math
Difficulty: easy
Interview Round: Technical Screen
## Prompt
In hypothesis testing:
1. Define **Type I error** and **Type II error**.
2. Explain how they relate to **significance level** \(\alpha\) and **power** \(1-\beta\).
3. Give a practical product/DS example where you would prioritize minimizing Type I vs Type II error, and why.
Quick Answer: This question evaluates understanding of hypothesis testing and statistical inference, focusing on definitions and implications of Type I and Type II errors and their relationship to the significance level (α) and statistical power (1−β).