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