In my post last week I talked about the importance of representative samples for making universal statements, including averages and percentages. But how big should your sample be? You don’t need to look at everything, but you probably need to look at more than one thing. How big a sample do you need in order to be reasonably sure of your estimates?

In my previous post, I discussed the differences between existential and universal statements. In particular, the standard of evidence is different: to be sure that an existential statement is correct we only need to see one example, but to be sure a universal is correct we have to have examined everything. But what if we don’t have the time to examine everything, and we don’t have to be absolutely sure?

There’s a famous story about swans that Nasim Taleb used for the title of his recent book. European zoologists had seen swans, and all the swans they had seen had white feathers, so they said that all the swans in the world were in fact white. Then a European went to Australia and saw swans with black feathers.

Over the past few years I’ve realized that there are a lot of scientists who have a different view of science than I do, and most of them don’t even know about my way of thinking. But my way of thinking about science – Instrumentalism – is cool! I’m writing this post to explain what Instrumentalism is, and why I prefer it to other ways of thinking about science.