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. Each chapter includes a short biographical note about a contributor to probability theory, exercises, and selected answers. Ancillary material is accessible online.
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. Each chapter includes a short biographical note about a contributor to probability theory, exercises, and selected answers. Ancillary material is accessible online.
Foreword. Preface. Sets, Events, and Probability. Finite Processes. Discrete Random Variables. General Random Variables. Statistics and the Normal Distribution. Conditional Probability. The Poisson Process. Randomization and Compound Processes. Entropy and Information. Markov Chains. Appendices. References. Index.
Foreword. Preface. Sets, Events, and Probability. Finite Processes. Discrete Random Variables. General Random Variables. Statistics and the Normal Distribution. Conditional Probability. The Poisson Process. Randomization and Compound Processes. Entropy and Information. Markov Chains. Appendices. References. Index.
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