 Type I and type II errors

Type I and Type II errors are concepts in statistics that describe the potential errors that can occur when testing a hypothesis. 1. **Type I Error (False Positive)**: This occurs when a null hypothesis (H0) is rejected when it is actually true. In simpler terms, it means that the test indicates a significant effect or difference when there actually is none.