Why might researchers set the significance level (alpha) at 0.01 instead of 0.05?

Setting the significance level (alpha) at 0.01 instead of 0.05 is primarily done to minimize the risk of a Type I error, which occurs when a researcher incorrectly rejects a true null hypothesis. By using a lower alpha level, researchers are indicating that they require stronger evidence to conclude that there is a significant effect or difference. This is particularly important in studies where a false positive could have serious implications, such as in medical research or other high-stakes fields.

In contrast, a higher alpha, like 0.05, means there is a greater chance of falsely declaring a significant result when, in fact, there isn't one. By adopting a stricter threshold at 0.01, researchers demonstrate a commitment to ensuring that results are reliable and robust before drawing conclusions. Therefore, selecting a lower significance level is a strategic choice aimed at safeguarding against misinterpretations of data.