In the realm of statistical testing, it's crucial to appreciate the potential for flawed conclusions. A Type 1 mistake – often dubbed a “false positive” – occurs when we reject a true null statement; 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 claim;