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Introduction to Probability

作者：Joseph K. Blitzstein, Jessica Hwang
原價：NT$ 1,600

ISBN：9781466575578
版次：1
年份：2014
出版商：Taylor & Francis
頁數/規格：580頁/精裝單色

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Description
Developed from celebrated Harvard statistics lectures, Introduction to Probability provides essential language and tools for understanding statistics, randomness, and uncertainty. The book explores a wide variety of applications and examples, ranging from coincidences and paradoxes to Google PageRank and Markov chain Monte Carlo (MCMC). Additional application areas explored include genetics, medicine, computer science, and information theory. The print book version includes a code that provides free access to an eBook version.

The authors present the material in an accessible style and motivate concepts using real-world examples. Throughout, they use stories to uncover connections between the fundamental distributions in statistics and conditioning to reduce complicated problems to manageable pieces.

The book includes many intuitive explanations, diagrams, and practice problems. Each chapter ends with a section showing how to perform relevant simulations and calculations in R, a free statistical software environment.

Features

Presents definitions, theorems, and proofs through stories that preserve mathematical precision and generality

Focuses on real-world relevance and statistical thinking

Includes interesting modern applications, such as Google PageRank, legal and medical examples, and applications of MCMC to ecology and cryptography

Explains and connects the most important distributions used in statistics

Contains nearly 600 exercises that reinforce understanding of the material instead of requiring repetitive calculations

Supplements key concepts with memorable diagrams

Explains how to run simulations, make visualizations, and perform statistical calculations using R, a free statistical software environment

Table of Contents
1. Probability and Counting
2. Conditional Probability
3. Random Variables and Their Distributions
4. Expectation
5. Continuous Random Variables
6. Moments
7. Joint Distributions
8. Transformations
9. Conditional Expectation
10. Inequalities and Limit Theorems
11. Markov Chains
12. Markov Chain Monte Carlo
13. Poisson Processes
A. Math
B. R
C. Table of Distributions
Bibliography
Index

Joseph K. Blitzstein, Harvard University ,Cambridge, Massachusetts, USA
Jessica Hwang, Stanford University, Stanford, California, USA

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