Probability Theory and Statistical Inference
Probability Theory and Statistical Inference
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9781316636374This major new textbook is intended for students taking introductory courses in probability theory and statistical inference. The primary objective of this book is to establish the framework for the empirical modeling of observational (nonexperimental) data. The text is extremely student friendly, with pathways designed for semester usage, and although aimed primarily at students at second-year undergraduate level and above studying econometrics and economics, Probability Theory and Statistical Inference will also be useful for students in other disciplines that make extensive use of observational data, including finance, biology, sociology and psychology.
- A major new textbook with global adoption potential on a central social scientific and statistical topic
- An easy to follow, up-to-date exposition including numerous examples, case studies and pathways designed to allow rigorous and intuitive study
- Spanos is a leading figure in econometrics teaching and research, with a very successful track record as an author
Reviews & endorsements
"The chapters are impressive because of their thoroughness and attention to detail. The writing is elegant. The problem sections at the ends of the chapters are both reinforcing and creatively challenging... The section on 'building block' stochastics is one of the best I have read... the treatment and presentation are refreshing in their clarity." Computing Reviews
"Undergraduate and graduate-level introductory textbook on probability theory and
Product details
January 2007Adobe eBook Reader
9780511037344
0 pages
0kg
136 tables
This ISBN is for an eBook version which is distributed on our behalf by a third party.
Table of Contents
- Preface
- 1. An introduction to empirical modelling
- 2. Probability theory: a modelling framework
- 3. The notion of a probability model
- 4. The notion of a random sample
- 5. Theoretical concepts and real data
- 6. The notion of a non-random sample
- 7. Regression and related notions
- 8. Stochastic processes
- 9. Limit theorems
- 10. From probability theory to statistical inference
- 11. An introduction to statistical inference
- 12. Estimation I: properties of estimators
- 13. Estimation II: methods of estimation
- 14. Hypothesis testing
- 15. Misspecification testing
- References
- Index.
