Adjust significance level for multiple comparisons.
Test Parameters
Corrected Alpha
Adjusted Significance Level
0.00500
P-values must be lower than this to be significant.
Uncorrected Risk (FWER)
40.13%
Prob. of at least one False Positive if you don't adjust.
Overview
The Bonferroni correction is a simple method to counteract the problem of multiple comparisons. It reduces the chance of obtaining false-positive results (Type I errors) when performing multiple statistical tests.
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Pro Tips
Use when you have a large number of tests (e.g., genomic studies) to avoid spurious significant findings.
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Fun Facts
"It is considered very conservative, meaning it greatly lowers the risk of false positives but increases the risk of false negatives (Type II error)."
"Corrected Alpha = Original Alpha / Number of Tests."
