The Hazard of Multiple Comparisons
The Hazard of Multiple Comparisons
The need to compare means of multiple datasets arises frequently in data analysis. Procedures such as ANOVA detect a difference among means but do not determine which of them are significantly different. We may be tempted to simply run -tests on each pair of means to detect these differences, but, as this Demonstration shows, doing so leads to a dramatic inflation of the true type I error (rate of false positives). Thus, when multiple comparisons are needed, a correction for this error inflation must be used.
t