Choosing a significance level involves balancing the risk of a Type I error and the consequences of making such an error. Here are some factors to consider:
- Impact of Error: If the consequences of a Type I error are severe, such as in life-threatening conditions, a lower significance level (e.g., 0.01) might be more appropriate. - Sample Size: Larger sample sizes can allow for a lower significance level without sacrificing statistical power. - Prior Research: Consider what previous studies have used. Consistency can help in comparing results across different studies.
