概率统计权威教材Probability and Statistics (2nd Edition)By Morris H. Degroot-经管之家官网!

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概率统计权威教材Probability and Statistics (2nd Edition)By Morris H. Degroot

概率统计权威教材Probability and Statistics (2nd Edition)By Morris H. Degroot

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ProbabilityandStatistics(2ndEdition)ByMorrisH.Degroot请注意是第二版的,最新的是第三版,国内有翻译版和删减版了Publisher:AddisonWesleyPublishingCompanyNumberOfPages:723PublicationDate:1986-01ISBN-10/ASI ...
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Probability and Statistics (2nd Edition)By Morris H. Degroot

请注意是第二版的,最新的是第三版,国内有翻译版和删减版了
Publisher: Addison Wesley Publishing Company Number Of Pages: 723 Publication Date: 1986-01 ISBN-10 / ASIN: 020111366X ISBN-13 / EAN: 9780201113662

Product Description:
The revision of this well-respected text presents a balance of the classical and Bayesian methods. The theoretical and practical sides of both probability and statistics are considered. New content areas include the Vorel- Kolmogorov Paradox, Confidence Bands for the Regression Line, the Correction for Continuity, and the Delta Method.




Summary: Solid text for the study of probability and statistics for math majors
Rating: 5
An earlier edition of this book was the text when I took my first course in probability and statistics. Now that I teach math and computer science at a small college I am always on the lookout for a new text and so I examined this book within that context. The coverage is at a high mathematical level; there are many theorems with proof. However, there are also many worked examples that demonstrate how the theorems are applied. The quality of the exposition is such that it is very readable for those who have gone through a three-semester calculus sequence.
The chapters are:

*) Introduction to probability
*) Conditional probability
*) Random variables and distributions
*) Expectation
*) Special distributions
*) Estimation
*) Sampling distributions of estimators
*) Testing hypotheses
*) Categorical data and nonparamentric methods
*) Linear statistical models
*) Simulation

A large set of problems appears at the end of each chapter and solutions to the odd-numbered ones are included in an appendix.
The high level of readability that I appreciated so much when I learned from an earlier edition has been maintained through this one. I can strongly recommend this book as a text for upper level courses in probability and statistics.



Summary: Fantastic Into Probability and Stats Book
Rating: 5
This book is a fantastic introduction to probability and statistics. It is clear and presents the material with lots of accompanying intuitive explanations. The book also has lots of great examples that clarify the theory and show how the theory can be applied. This book has a strong focus on Bayesian methods, so it is a good place to start if you are trying to learn Bayesian statistics. I love this book.



Summary: The truth about this book. 99% of other great reviews are bogus.
Rating: 2
This book was not written for students. It was written so that the author can gain respect from his from his academic peers. The explanations are absolutely horrible. It purposely explains simple concepts in overly verbose, complicated ways. The idea is to make the subject appear as complicated as possible when it doesn't need to be. It reads like those academic papers that are purposely written in overly complicated language so that nobody understands what the author is talking about except the author himself. The idea is to impress his academic circle by showing that he did a "complicated" analysis.

When are these people going to learn that "simplicity is the ultimate sophistication" - Da Vinci?

Here's an example. Do you know what's a percentile? Think about your SAT or GRE score report. 80th percentile means 80% of the people scored lower than you. 90th percentile means 90% of the people scored lower than you. Simple, right? This book introduces the concept like this:

"The d.f. of a random variable X gives us the probability that X<=x for all real numbers x. It is often the case that we choose a probability, like 1/2, and we want to know where in the distribution of X we can find that probability. For example, suppose that X is the amount of rain that will fall tomorrow and we want to place an even-money bet on X as follows. If X<=x0, we win one dollar and if X>x0 we lose one dollar. In order to make this bet fair, we need Pr(X<=xo)=Pr(X>x0)=1/2. We could use all the real numbers x trying to find one such that F(x)=1/2, and then we could let x0 equal the value we found. If F is a one-to-one function, then F has an inverse F^-1 and x0=F^-1(1/2)." - P.114

Lol! If you want to learn like this, go ahead and buy this book. I'll give this book two stars because there are probably a few souls out there who actually do prefer to learn like this.



Summary: Best intro reference for graduate students
Rating: 5
This is by far the best graduate text for basic probability and statistics that is currently made. It even nicely incorporates Bayesian material in a completely relevant way. No, it is probably too complex and abstract for complete beginners in probability as many of the reviewers here have suggested. For anyone with even just a basic background in statistics or probability, however, it is perfect. It is straightforward, comprehensive and most importantly highly readable. There is no comparison to other probability/statistics texts I own--if you are pursuing any sort of graduate level study in statistics or basic probability this the textbook to own and reference.



Summary: Good
Rating: 5
Its a really good book for starters, especially with a weak background in math.. it may be little too exhaustive but overall I think its a good deal!!!


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