Sometimes the choice of statistical philosophy is decided by convention or convenience. . . . In many settings, however, we have freedom in deciding how to attack a problem statistically. How then do we decide how to proceed?
Schools of statistical thoughts are sometimes jokingly likened to religions. This analogy is not perfect—unlike religions, statistical methods have no supernatural content and make essentially no demands on our personal lives. Looking at the comparison from the other direction, it is possible to be agnostic, atheistic, or simply live one’s life without religion, but it is not really possible to do statistics without some philosophy. Even if you take a Tukeyesque stance and admit only data and data manipulations without reference to probability models, you still need some criteria to evaluate the methods that you choose.
One way in which schools of statistics are like religions is in how we end up affiliating with them. Based on informal observation, I would say that statis- ticians typically absorb the ambient philosophy of the institution where they are trained—or else, more rarely, they rebel against their training or pick up a philosophy later in their career or from some other source such as a persuasive book. Similarly, people in modern societies are free to choose their religious affiliation but it typically is the same as the religion of parents and extended family. Philosophy, like religion but not (in general) ethnicity, is something we are free to choose on our own, even if we do not usually take the opportunity to take that choice. Rather, it is common to exercise our free will in this setting by forming our own personal accommodation with the religion or philosophy bequeathed to us by our background.
For example, I affiliated as a Bayesian after studying with Don Rubin and, over the decades, have evolved my own philosophy using his as a starting point. I did not go completely willingly into the Bayesian fold—the first statistics course I took (before I came to Harvard) had a classical perspective, and in the first course I took with Don, I continued to try to frame all the inferential problems into a Neyman-Pearson framework. But it didn’t take me or my fellow students long to slip into comfortable conformity. . . .
Beliefs and affiliations are interesting and worth studying, going beyond simple analogies to religion.
P.S. See here for some similar thoughts from a few years ago. The key point is that a belief is not (necessarily) the same thing as a religion, and I don’t think it’s helpful for people to use “religion” as a generalized insult that is applied to beliefs that they disagree with.