In statistical hypothesis testing, researchers commonly use an α-level of 0.05 as the threshold for determining statistical significance. However, the choice of α-level depends on the context of the research and the consequences of making a Type I error (false positive). 

1.  Lower α-Levels: Consider scenarios where a lower α-level (e.g., 0.01) might be more appropriate. What types of experiments or decisions would require this higher level of certainty? For example, think about situations where the consequences of a false positive could be severe or costly. Provide your rationale.
2. Higher α-Levels: In contrast, when might a higher α-level (e.g., 0.10 or 0.20) be acceptable? Reflect on contexts where being overly cautious might lead to missed opportunities or where the stakes of a false positive are lower. Provide your rationale.

Initial discussion question posts should be a minimum of 200 words and cite at least two references using APA style.