This article is based on his book Uncertainty (2016), which is a collection of various arguments about probability and statistics. Some of his arguments in the

This article is based on his book Uncertainty (2016), which is a collection of various arguments about probability and statistics. Some of his arguments in the book are fairly well presented and some of them I agree with (not perfectly overlapping sets). His view of probability is sort of a combination of objective Bayesianism and logical probability. He argues that all probability is conditional on some evidence, so it is meaningless to talk of the probability of a proposition in isolation from others. Further, since probability analysis is based on relations between propositions, it is actually a part of logic. He belongs to the group who want to see hypothesis testing banished from statistics. The vast literature on that issue is easy to find. The big change he wants to see in statistics is to follow a more machine learning approach. Develop models against a sample set, then test them against a testing set rather than against some ideal distribution.