The Signal and the Noise. It's a fascinating book about statistics and probability, from a statistician whose track record in predicting American elections is remarkably accurate.
Though he's despised by the pundit-class, particularly those on the right wing who've been recently stymied by his predictions, Silver comes across as remarkably nonpartisan. He cares about data, and being as accurate as possible. Period.
One thing I most certainly did not expect as I read through Silver, though, was just how much theology would be involved. This goes well beyond the opening chapters, where he spends page after page discussing the Reformation. It goes beyond his quoting Proverbs.
Silver is a Bayesian statistician, meaning his approach to interpreting data is probabilistic and flexible. Bayesian statistics derive their name from Thomas Bayes, an eighteenth century Presbyterian minister/mathematician. Bayes created a theorem that calculates the likelihood of things, a theorem that he derived from a theological treatise on the nature of God's sovereignty.
This was beyond cool, and it took my reflections to interesting places. Silver's explication of probability theory and Bayes essay on the nature of the divine play out interestingly against the theological implications of Many Worlds theory.
Silver spends a great deal of time talking about probability in the context of gambling. I'm not a gambling man myself. First, it doesn't float my boat, and second, I've watched gambling destroy too many lives and relationships. More on that another time.
But there's one wager I know that might be interestingly informed by a fusion of Bayesian thinking and the Many Worlds Interpretation. It's the wager suggested by Blaise Pascal. That classic wager is also itself a probabilistic statement. To woefully oversimplify it, Pascal's Wager suggests that there is nothing to be lost by believing in a God if God does not exist, and much to be potentially be lost if you do not believe and God turns out to be there. Therefore, belief is a more rational position.
This has always struck me as a bit weak, if only because it seems too self-interested and abstracted.
Applying the Bayesian Theorem to belief in the probability of a God is a related but different wager. Bayes laid out the probability of a thing in terms of an equation, which is perhaps one reason most human beings struggle with it. I fiddled around with a spreadsheet for a bit the other day, trying to figure out what elements might make for an interesting probabilistic proof. What factors should be considered in calculating the probability of God? Hmm. Good question.
Faith as a transcultural phenomenon? Sure. But the absence of empirically measurably evidence needs to be in there. So do the belief patterns of scientists. I mucked around for a little bit, assigning factors and percentages. I was as conservative as possible, and as contrarian to my own faith-position as possible. With the most pessimistic assumptions used as primary metrics, I ended up with a rather low probability for God's existence. Not "impossible." Just "highly improbable."
This was not news. It's why faith requires a Kierkegaardian existential leap, eh?
Where the equation got interesting was when I took it beyond the assumption of one space and time, and into the multiverse. As Stephen Hawking spitballed it, there might be...at least...10 to the 500 discrete universes. Assuming they're not functionally infinite. What I found?
Taking a Bayesian probabilistic equation and playing it out across ten to the 500 iterations, the answer is pretty much always yes.
The House always wins, baby. The House always wins.