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I only learned about this book relatively recently so I cannot claim that this has influenced my way of thinking about my field. However, given my research interests—I do like to think of myself of a stochastic modeler of scientific data—and the fairly unique combination of topics and ideas covered, it was not hard to select this book as one that perhaps best characterizes my research interests and the way I like to think about statistics and science. The book covers probability theory, starting with a philosophical discussion of the notion of uncertainty, crossing over from notions of input uncertainty, which is the way deterministic modelers often like to think, to the more probabilistic/statistical notion of uncertainty as a result of actual randomness in the system. The book also discusses Markov chains and Markov random fields, touching upon both Markov chain Monte Carlo and spatial modeling, two of my primary research interests. Throughout, with the help of interesting scientific examples, the author connects probabilistic and statistical thinking to scientific problems. I hope to spend much of my research career working on statistical research motivated by science, and it is precisely the combination of philosophy, probability, scientific thinking, computing and mathematics, as discussed in this book, that makes statistics such a fascinating field of study for me.