Intermediate Statistics and Econometrics: A Comparative Approach | 
 enlarge | Author: Dale J. Poirier
Publisher: The MIT Press
Category: Book
List Price: $50.00
Buy New: $16.93
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Rating:  7 reviews
Sales Rank: 337164
Media: Hardcover
Pages: 731
Number Of Items: 1
Shipping Weight (lbs): 3.6
Dimensions (in): 10.4 x 7.4 x 2
ISBN: 0262161494
Dewey Decimal Number: 330.015195
EAN: 9780262161497
Publication Date: March 10, 1995
Availability: Usually ships in 1-2 business days
Condition: NEW - excellent, clean condition - hard bound, The MIT Press, 1995***
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Product Description
The standard introductory texts to mathematical statistics leave the Bayesian approach to be taught later in advanced topics courses -- giving students the impression that Bayesian statistics provide but a few techniques appropriate in only special circumstances. Nothing could be further from the truth, argues Dale Poirier, who has developed a course for teaching comparatively both the classical and the Bayesian approaches to econometrics. Poirier's text provides a thoroughly modern, self-contained, comprehensive, and accessible treatment of the probability and statistical foundations of econometrics with special emphasis on the linear regression model.
Written primarily for advanced undergraduate and graduate students who are pursuing research careers in economics, Intermediate Statistics and Econometrics offers a broad perspective, bringing together a great deal of diverse material. Its comparative approach, emphasis on regression and prediction, and numerous exercises and references provide a solid foundation for subsequent courses in econometrics and will prove a valuable resource to many nonspecialists who want to update their quantitative skills.
The introduction closes with an example of a real-world data set -- the Challenger space shuttle disaster -- that motivates much of the text's theoretical discussion. The ten chapters that follow cover basic concepts, special distributions, distributions of functions of random variables, sampling theory, estimation, hypothesis testing, prediction, and the linear regression model. Appendixes contain a review of matrix algebra, computation, and statistical tables.
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| Customer Reviews: Read 2 more reviews...
 A Good Comparison of the Frequentist and Bayesian Approaches March 30, 2001
Steve J Verdon (California)
8 out of 10 found this review helpful
This book takes the reader through the basics of probability theory right in through sampling theory, estimation, hypothesis testing, and regression analysis, and at the same time puts both the Classical and Bayesian approaches side by side, so that the reader can see the strengths and weaknesses of both approaches. This book is an excellent for both advanced undergraduates and graduate students interested in applied empirical research.
Please add table of contents... May 9, 2002
1 out of 6 found this review helpful
How can you expect people to buy this book without table of contents?!
please give us a table of contents May 14, 2002
1 out of 7 found this review helpful
How can you expect us to buy the book without providing a table of contents?!
Econmetrics06 November 16, 2006
Y. Sun (Guelph, Ontario Canada)
This is an excellent textbook. It provides many useful exercises and you can find most of the classic statistic theories. So many years have passed since I bought this book and I find myself very often to reread some chapters each year. THe more I learn about the statistics and econometric theory, the more I realize how good this book is.
 A Very Good Reference Book October 1, 2004
jaar330 (California)
2 out of 3 found this review helpful
We were taught by Prof. Poirier himself; so this was the required text for the course. We hated the book (initially) and called it "the purple monster" and so on, but by the end of the course we realized that it was indeed one of the best reference books available- and I really mean it. No other book covers material like this one does - from both, the Classical and Bayesian perspectives. To some, this book might come across as very technical, so you could/should refer to Gary Koop (Bayesian stuff) and perhaps "Hogg and Craig" or the book by "Mood, Graybill and Boes" (for Classical stuff).
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