In an update Caplan shared correspondence from Applied Divinity Studies suggesting that the main value of including quantitative evidence is not that the reader will be persuaded after reviewing the numbers.

One benefit to number-crunching is that the researcher may change their understanding after carefully combing through the evidence. ADS looked into San Francisco shoplifting and found that the data do not support popular perceptions of a crime surge.

The other benefit to including spreadsheets is that it promotes a kind of reputational social trust. Most of the audience, including experts, won't carefully review numerical evidence that took months to compile. But there is a reputational reward available to anyone who can discredit a public figure by finding embarrassing errors in their work. Even an amateur with no field expertise can point out falsified figures and arithmetic anomalies.

Hence Alexey Guzey launched his science career by debunking Why We Sleep.

And Dan Ariely took a reputational hit when one of his studies on honesty was found to contain fraudulent data.

It's easy to make vague explanations and predictions that can't be checked with facts. Including quantitative evidence suggests confidence by increasing the attack surface provided to adversaries.

Caplan's blog is named "Bet On It" because of his conviction that "bets are one of the best ways to (a) turn vague verbiage into precise statements, and (b) discover the extent of genuine disagreement about such precise statements."