Experimental Research Questions
There are several ways to control for Type I error in experimental research. One common method is to set a predetermined significance level, typically denoted as alpha (α), which represents the maximum acceptable probability of committing a Type I error. By choosing a lower alpha level, such as 0.05 or 0.01, researchers can reduce the likelihood of falsely rejecting the null hypothesis. Another approach is to use multiple comparison procedures, such as Bonferroni correction or Tukey's Honestly Significant Difference (HSD) test, which adjust the significance level for multiple comparisons to maintain an overall alpha level. Additionally, researchers can employ statistical techniques like p-value adjustments, such as the Benjamini-Hochberg procedure, to control for Type I error when conducting multiple hypothesis tests.