Type 1 and type 2 errors

Key parameters & explanaition

• Type I error: Concluding there is an effect when there actually isn’t (false positive).
• Type II error: Failing to detect a real effect that does exist (false negative).

Examples

Quick real-world (COVID test style):

• TP: Sick + test positive
• FP: Healthy + test positive
• TN: Healthy + test negative
• FN: Sick + test negative