ABSTRACT
Everybody changes their mind. The distinction is not always so clear in practice – even the authors apply both philosophies in their work, and thus don't identify with a single label. Probability theory is central to every statistical analysis. A very strict frequentist interpretation might even conclude the pollster is just wrong. A less extreme frequentist interpretation, though a bit awkward, is more reasonable: in long-run hypothetical repetitions of the election, i.e., elections with similar circumstances, candidate A would win roughly 90% of the time. The idea of allowing one's prior experience to play a formal role in a statistical analysis might seem a bit goofy. Though Bayes developed his philosophy during the 1740s, it wasn't until the late twentieth century that this work reached a broad audience.
