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This text presents R programs and animations to provide an intuitive yet rigorous understanding of how to model natural phenomena from a probabilistic point of view. It centers on viewing probability as a way to look at the world and shows how to combine and link stochastic processes to form more complex processes that are better models of natural phenomena. The text also covers the Poisson process, transforms, Bayesian networks, entropy and information, and Markov chains. Each chapter includes a short biographical note about a contributor to probability theory, exercises, and selected answers. Ancillary material is accessible online.
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