ISBN0534399428

This is an absolutely fantastic book, written by one of the best professors I've ever had for a technical class. I took Prof. Rice's course, Stat 135, at UC Berkeley and it was a really great and illuminating experience. The book, the lectures, and the course overall, cemented my decision to become a Statistics major. The book is technical, but very accessible, and contains applications ranging from Astrophysics to Jane Austen to Finance to Biology and more. It is ideal for self study and exceedingly interesting to just sit down and read. The difficulty level of the problems is fairly distributed such that slow learners have a chance to acclimate themselves to the material, and the quicker ones of us can look to the later problems and be sufficiently challenged.

Don't believe the reviews here or the ones on [...]. They're just outright wrong. This is a great book written by a great professor. If it's over your head, then maybe you don't realize it is written for an upper division Mathematical Statistics course.

My professor used this as a text for a graduate overview of mathematical statistics course, with no prior experience in statistics required.

However, this book is not for the neophyte in statistics, and would have DEFINITELY benefited from a accompanying manual with extra problems and FULLY WORKED SOLUTIONS. Needless to say the problems in the book, although plentiful, although informative, were not what I would consider easily approachable to non-statistical gurus.

Also, I felt the organization of the book could have been better. A section in each chapter clearly outlining the concepts would have been nice.

But, if you have a great professor, and other references on hand, then yes, you could make good use of this book.

This book got very mixed reviews from 1 star to 5. I am in agreement with Froese's review and give it 4 stars. Rice is trying to write a book for statistics students who are not mathematics or statistics majors without shortchanging them on the advanced topics and the theory. This can be difficult and often alienates both the beginners and those interested in advanced methods. I have tried to stay along that fine line with my texts also. So I appreciate the difficulties. As an author of a book on bootstrap methods, I also appreciate the way Rice has integrated that subject into this text.

This is the poorest class text book I have ever seen.

First of all, it rarely extracts a theoretical description of a term or an idea but mixed everything into lousily long examples. You will constantly see statements like "to see what is ***, let us first see this example..." then after pages of meaningless details of the example, you still don't know what *** is!!! This makes learning very ineffective. This is not what a MATH book is supposed to be.

The second big problem is the consistency. The book is clearly written by different people and loosely put together like a Jigsaw Puzzle. Symbols vary from sections to sections, or even paragraphs from paragraphs (e.g. the R and T in 11.2.3). This can confuse you a lot even though the idea is pretty straightforward.

The practice problems of the book are not helpful. Most of them are extremely long and there is no fairly basic practice. Every problem is like a small project, or a big one. I have an engineering background thus I coded with MATLAB for solving these problems. I cannot imagine how beginners, especially college undergraduates, can "learn" statistics with this book.

There are a lot of harmful typos too, though the Errata page corrected some of them. That is not enough!

In all, the ideas and methods introduced in the book is nothing different from others, but the organization and structure is horrible. Never use this book if you are a beginner and really want to learn what Statistics is.

This book is absolutely terrible. There is no way that this book is more than 2 stars. You will not understand this book unless you already have significant knowledge of theoretical statistics. It's an introductory theoretical statistics book that assumes you already have a lot of knowledge of theoretical statistics! The intuitive and mathematical explanations are extremely poor. I'll give a simple example that anyone can understand. In statistics, expected value means the average of the numbers. If you have three numbers (1, 2, and 3), the expected value is the average of those three numbers (1+2+3)/3 = 2. Simple, right? Expected value = average. Period. This book explains expected value like this: expected value is parallel to the notion of weighted average... omg! This example isn't so bad because everyone understands the concept of averages. Imagine what you'll go through when he attempts to explain other concepts that are much more difficult. Studying statistics does not need to be this way. Any professor who chooses this book is either gaining personally from the sales of this book, does not care at all about the students, or intentionally making it difficult for the students.