Um, I don't think the null hypothesis is usually phrased as, "There is no effect and our data wasn't unusual" and then you conclude "our data was unusual, rather than there being no effect" when you get data with probability < .05 if the Sun hasn't exploded. This is not a fair steelmanning.
I don't follow. The null hypothesis can be phrased in all sorts of ways based on what you want to test - there there's no effect, that the effect between two groups (eg. a new drug and an old drug) is the same etc.
then you conclude "our data was unusual, rather than there being no effect" when you get data with probability < .05 if the Sun hasn't exploded.
I don't know that my frequentist example does conclude the 'data was unusual' rather than 'there was an effect'. I am not sure how a frequentist would break apart the disjunction, or indeed, if they even would without additional data and assumptions.
http://xkcd.com/1132/
Is this a fair representation of frequentists versus bayesians? I feel like every time the topic comes up, 'Bayesian statistics' is an applause light for me, and I'm not sure why I'm supposed to be applauding.