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This 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.
- Sales Rank: #10322513 in Books
- Brand: Brand: Cambridge University Press
- Published on: 1999-10-13
- Original language: English
- Number of items: 1
- Dimensions: 9.72" h x 1.73" w x 6.85" l, .39 pounds
- Binding: Hardcover
- 844 pages
Features
- Used Book in Good Condition
Review
"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
About the Author
Aris Spanos is Wilson Schmidt Professor of Economics at Virginia Tech. He has also taught at Birkbeck College, London, the University of Cambridge, the University of California and the University of Cyprus. Professor Spanos is the author of Probability Theory and Statistical Inference (1999) and Statistical Foundations of Econometric Modeling (1986), both published by Cambridge University Press. Professor Spanos's research has appeared in journals such as the Journal of Econometrics, Econometric Theory, Econometric Reviews, and Philosophy of Science. His research interests include the philosophy and methodology of statistical inference and modeling, foundational problems in statistics, statistical adequacy, misspecification testing and respecification, resampling and simulation techniques and modeling speculative prices.
Most helpful customer reviews
21 of 22 people found the following review helpful.
the best foundation in stats imaginable
By Louis Charbonneau
This book is absolutely remarkable.
It presents the material traditionally taught in the second-year statistics (but actually goes well beyond, e.g. stochastic processes) and will be of interest to all people interested to (re-)learn statistics well, either undergraduates, or advanced students of any level. Professors should also read it maybe use it in class. Students will thank them.
The author took more than 14 years to polish it, and I would bet that scholars of pedagogy will put this book as an example of the highest possible level of their discipline. I would also bet that this book will have a long and brilliant career in statistical education. On gets the feeling that the author gave the same care and energy to the elaboration of this book as people commonly give to research.
The author is also a man with a mission. In his preface, one can read with pleasure and disbelief a passionate attack on the dumbing-down of undergraduate education in Europe and America. Having taught undergrads in commerce with the "predigested pap" he is talking about, I can really relate to the frustration of the author. There is no dilution of material or dumbing down here: all the ugly details are given, which makes that book not only a pedagogical tool but also a great reference.
There is no book on the market that is so polished in both presentation and discussion, that exposes intermediate stats at such an intelligent, comprehensive level, and finally that uses the historical development to project such clarity on the actual state of the science. I would say the closest competitor to this book is the great volume "Intermediate Statistics" by Dale Poirier, which has more econometrics and which might be a bit more comprehensive on the bayesian side, but the main focus of this one is on UNDERSTANDING and SYNTHESIZING. By the way, the focus of this book is statistics, not econometrics, despite the fact that the author has written extensively in econometrics.
I wish I would be an undergrad again and re-learn statistics with this book. Nevertheless, readers of all levels will learn something from it.
Ah, and the price is right. Value for your money!
14 of 15 people found the following review helpful.
Spanos -- bigger, better
By Scott de Marchi
Like many, I used the 1986 big green Spanos book to learn econometrics. Simply put, this latest follows the course charted by the first book -- it first covers probability theory, and then uses this to motivate the modelling portion of the book. Unlike the 1986 book, which was terse in places, this monograph is much more comprehensive. It isn't so much that new subjects are covered (though some are), but the current treatment far surpasses the 1986 book. More graphs, to aid geometric intution, are included. More text discusses the implications of the mathematics. More useful, in short, for a graduate student trying to learn econometrics. The only book I think is in this class is DeGroot, and that book suffers from little attention paid to econometrics (though it does do the probability material quite well).
Highly, highly recommended. And one other bonus: Spanos discusses in the introduction why he refuses to water things down, and even has a quote from the mathemetician Binmore.
3 of 3 people found the following review helpful.
great book
By E. Sinha
the book is great for anybody who wants to know the foundations of statistical and probability modelling. it covers all aspects of modelling like defining a statistical space, probability model, estimation, inference and its chapters on stochastic process were very informative. It was a great learning experience through this book. Basically it explains why we do it and how we do it
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