Sublime

But how do we decide which information to disregard,

probabilities attach themselves to the descriptions of events and not to events themselves.

What’s interesting about blockchain instead is that it enables “frictionless binding contracts,” to use the language of economics.

Why are more complicated explanations less likely to be true? Let’s work it out mathematically. Take two competing explanations, each of which seem to equally explain a given phenomenon. If one of them requires the interaction of three variables and the other the interaction of thirty variables, all of which must have occurred to arrive at the stat

Today we can answer such questions by referring to the causal diagram and checking which variables produce a discrepancy between P(Y | X) and P(Y | do(X)).

Learning means trying to select the simplest model that fits the data. Suppose I show you the top card and tell you that the three objects surrounded by thick lines are “tufas.” With so little data, how do you find the other tufas? Your brain makes a model of how these forms were generated, a hierarchical tree of their properties, and then selects

Over the course of several summers in the late 1960s, Baum and Lloyd Welch, an information theorist working down the hall, developed an algorithm to analyze Markov chains, which are sequences of events in which the probability of what happens next depends only on the current state, not past events.

Thomas Bayes was an English minister who was probably born in 1701—although it may have been 1702. Very little is certain about Bayes’s life, even though he lent his name to an entire branch of statistics and perhaps its most famous theorem.

Philip was the first economist to make use of his son’s invention of path diagrams.