In the realm of hypotheses testing, it's crucial to recognize the potential for faulty conclusions. A Type 1 false positive – often dubbed a “false alarm” – occurs when we reject a true null hypothesis; essentially, concluding there *is* an effect when there isn't one. Conversely, a Type 2 error happens when we can't reject a false null sta