Introduction to probability with R / Kenneth Baclawski
Material type:
TextSeries: Text in statistical science ; 75Publication details: Boca Raton : Chapman & Hall, 2008 Description: XVI, 363 p. : il. ; 24 cmISBN: 1-4200-6521-1Subject(s): Estadística matemática | Modelos matematicos | R (Lenguaje de programación) | ProbabilidadesSummary: Based on the popular probability course by Gian-Carlo Rota of MIT, "Probability and Random Processes with R" provides a calculus-based introduction to probability. The text systemically motivates and organizes the standard distributions that most often occur in probability using physical processes. Presenting a probabilistic approach that builds on other approaches such as geometry and physical processes, the book addresses sets, events, and probability; finite processes; random variables; statistics and normal distribution; conditional probability; the Poisson process; entropy and information; Markov chains; Markov processes; Bayesian networks; and the Bayesian web. Various exercises and examples compare different perspectives.Summary: Índice: 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.
| Item type | Home library | Call number | URL | Status | Date due | Barcode | Item holds |
|---|---|---|---|---|---|---|---|
| Monografías | 02. BIBLIOTECA CAMPUS PUERTO REAL | 519.21/BAC/int (Browse shelf(Opens below)) | Texto completo | Checked out | 31/01/2024 | 374272705X |
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Bibliografía: p. 355
Based on the popular probability course by Gian-Carlo Rota of MIT, "Probability and Random Processes with R" provides a calculus-based introduction to probability. The text systemically motivates and organizes the standard distributions that most often occur in probability using physical processes. Presenting a probabilistic approach that builds on other approaches such as geometry and physical processes, the book addresses sets, events, and probability; finite processes; random variables; statistics and normal distribution; conditional probability; the Poisson process; entropy and information; Markov chains; Markov processes; Bayesian networks; and the Bayesian web. Various exercises and examples compare different perspectives.
Índice: 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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