An Introduction to Probability and Statistical Inference
- 3rd Edition - May 22, 2024
- Author: George G. Roussas
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 1 8 7 2 0 - 9
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 1 8 7 2 1 - 6
An Introduction to Probability and Statistical Inference, Third Edition guides the reader through probability models and statistical methods to develop critical-thinking skills… Read more
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An Introduction to Probability and Statistical Inference, Third Edition guides the reader through probability models and statistical methods to develop critical-thinking skills. Written by award-winning author George Roussas, this valuable text introduces a thinking process to help users obtain the best solution to a posed question or situation and provides a plethora of examples and exercises to illustrate applying statistical methods to different situations.
- Offers a relatively rigorous, yet accessible, mathematical discussion of probability theory and statistical inference important to students in a broad variety of disciplines
- Includes relevant proofs and exercises with useful hints to their solutions
- Provides brief answers to even-numbered exercises at the back of the book and detailed solutions to all exercises available to qualified instructors in the solutions manual
Advanced students taking courses on Probability & Statistical Inference Researchers and academics across math, engineering, physical and life sciences, who require advanced coverage on the subject
1. Some Motivating Examples and Some Fundamental Concepts
2. The Concept of Probability and Some Basic Results
3. Numerical Characteristics of a Random Variable, Some Special Random Variables
4. Joint and Conditional p.d.f.'s, Conditional Expectation and Variance, Moment Generating Function, Covariance and Correlation Coefficient
5. Independence of Random Variables and Some Applications
6. Transformation of Random Variables
7. Some Modes of Convergence of Random Variables, Applications
8. An Overview of Statistical Inference
9. Point Estimation
10. Confidence Intervals and Confidence Regions
11. Testing Hypotheses
12. More About Testing Hypotheses
13. A Simple Linear Regression Model
14. Two Models of Analysis of Variance
15. Some Topics in Nonparametric Inference
16. Appendix
2. The Concept of Probability and Some Basic Results
3. Numerical Characteristics of a Random Variable, Some Special Random Variables
4. Joint and Conditional p.d.f.'s, Conditional Expectation and Variance, Moment Generating Function, Covariance and Correlation Coefficient
5. Independence of Random Variables and Some Applications
6. Transformation of Random Variables
7. Some Modes of Convergence of Random Variables, Applications
8. An Overview of Statistical Inference
9. Point Estimation
10. Confidence Intervals and Confidence Regions
11. Testing Hypotheses
12. More About Testing Hypotheses
13. A Simple Linear Regression Model
14. Two Models of Analysis of Variance
15. Some Topics in Nonparametric Inference
16. Appendix
- Edition: 3
- Published: May 22, 2024
- Language: English
GR
George G. Roussas
George G. Roussas earned a B.S. in Mathematics with honors from the University of Athens, Greece, and a Ph.D. in Statistics from the University of California, Berkeley. As of July 2014, he is a Distinguished Professor Emeritus of Statistics at the University of California, Davis. Roussas is the author of five books, the author or co-author of five special volumes, and the author or co-author of dozens of research articles published in leading journals and special volumes. He is a Fellow of the following professional societies: The American Statistical Association (ASA), the Institute of Mathematical Statistics (IMS), The Royal Statistical Society (RSS), the American Association for the Advancement of Science (AAAS), and an Elected Member of the International Statistical Institute (ISI); also, he is a Corresponding Member of the Academy of Athens. Roussas was an associate editor of four journals since their inception, and is now a member of the Editorial Board of the journal Statistical Inference for Stochastic Processes. Throughout his career, Roussas served as Dean, Vice President for Academic Affairs, and Chancellor at two universities; also, he served as an Associate Dean at UC-Davis, helping to transform that institution's statistical unit into one of national and international renown. Roussas has been honored with a Festschrift, and he has given featured interviews for the Statistical Science and the Statistical Periscope. He has contributed an obituary to the IMS Bulletin for Professor-Academician David Blackwell of UC-Berkeley, and has been the coordinating editor of an extensive article of contributions for Professor Blackwell, which was published in the Notices of the American Mathematical Society and the Celebratio Mathematica.
Affiliations and expertise
University of California, Davis, USARead An Introduction to Probability and Statistical Inference on ScienceDirect