pvals are a lot like the weather - everyone complains about it, nobody does anything about it. Specifically, what tends to be missing from these conversations i

pvals are a lot like the weather - everyone complains about it, nobody does anything about it. Specifically, what tends to be missing from these conversations is a good alternative - the author seems to be asking for false discovery rates/q values. Or maybe effect sizes? The reality is one size doesn't fit all, and the most useful statistic depends on the context. Oh, and the target: good luck submitting your work to a biological journal without pvals. I'm sure the editor will briefly marvel at your courage in taking a stand as she rejects without review. While we're on the subject: there's a tendency to appeal to larger sample sizes, as the author also mentions. Worth remembering that for some of us data isn't a thing you download from the interweb, it's something you generate - and it costs money and time to do so. (And for human subjects research, the stakes are even higher...)