Probability and Statistics by Michael Evans & Jeffrey Rosenthal
Probability and Statistics - Table of Contents
- 1. Probability Model
- 2. Random Variables and Distributions
- 3. Expectation
- 4. Sampling Distributions and Limits
- 5. Statistical Inference
- 6. Likelihood Inferences
- 7. Bayesian Inference
- 8. Optimal Inferences and Hypotheses
- 9. Relationships Among Random Variables
- 10. Stochastic Processes and MCMC
What You Will Learn in Probability and Statistics
Probability and Statistics: The Science of Uncertainty by Michael J. Evans and Jeffrey S. Rosenthal is a acclaimed university-level textbook that bridges the gap between rigorous mathematical probability and practical statistical inference. This modern textbook breaks down complex concepts like Markov chain Monte Carlo (MCMC) methods, likelihood theory, and Bayesian inference into clear, manageable steps. Designed for undergraduate and graduate students, it connects abstract theory directly to real-world data analysis.
Perfect for mathematics, statistics, and computer science students, this textbook develops both foundational theory and computational techniques side by side. The authors explain key concepts using accessible language, detailed proofs, and extensive worked examples. Whether you are building a foundation in statistical theory or applying probabilistic models to complex algorithms, this text provides a thorough, step-by-step roadmap through every topic.
Recognized globally for its clarity, logical organization, and emphasis on computational reasoning, it remains one of the best probability and statistics books pdf available. It balances mathematical rigor with intuitive explanations, making it an essential resource for mastering modern statistical methods with confidence.
Book Details & Specifications
Title:
Probability and Statistics by Michael Evans & Jeffrey Rosenthal
Publisher:
W. H. Freeman & Co.
Year:
2023
Pages:
774
Type:
PDF
Language:
English
ISBN-10 #:
1429224622
ISBN-13 #:
978-1429224628
License:
External Educational Resource
Amazon:
Amazon
About the Author: Michael J. Evans
The author Michael J. Evans
and Jeffrey S. Rosenthal are distinguished professors in the Department of Statistical Sciences at the University of Toronto. Michael Evans has published extensively on Bayesian inference, foundational statistics, and decision theory. Jeffrey Rosenthal is a world-renowned expert in Markov chain Monte Carlo algorithms and stochastic processes, and is also widely known for his popular mathematics books.
Combining decades of teaching experience and cutting-edge research, Evans and Rosenthal have authored influential learning resources that make advanced probability and statistics accessible to students worldwide. Their joint work on probability theory and statistical inference provides a rigorous, computationally grounded foundation for modern quantitative analysis.
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