Constraining Bayes

Bayesian statistics are often presented as a better, modern alternative to the Frequentist approaches centred around NHST and the resulting obsession with statistical significance. This chapter outlines the basic ideas of Frequentist and Bayesian statistics. It raises critiques of the Frequentist approach but also points out constraints on the Bayesian approach that are often omitted or overlooked. In particular, the chapter discusses how both Bayesian and Frequentist approaches rely on a move from statistical hypotheses to substantive hypotheses that cannot be justified by consideration of the statistics alone. Instead, both approaches can lead to sound knowledge through a care for data analysis, tied to the experiments that generate the data.