A Test by Any Other Name: P

The exchange between Hoitjink, van Kooten and Hulsker (in press) (HKH) and Morey, Wagenmakers, and Rouder (in press) (MWR) in this issue is focused on the use of Bayes factors for statistical inference but raises a number of more general questions about Bayesian and frequentist approaches to inference. This note addresses recent negative attention directed at p-values, the relationship of confidence intervals and tests, and the role of Bayesian inference and Bayes factors, with an eye towards better understanding these different strategies for statistical inference. We argue that researchers and data analysts too often resort to binary decisions (e.g., whether to reject or accept the null hypothesis) in settings where this may not be required