Rating: 
Summary: Not enough
Review: This is the textbook used for the introductory statistics course for engineers at UC Berkeley and while it has some merits there are other textbooks that are better for the purpose:
If probability is the emphasis, Jim Pitman's Probability does the job.
If an overview is desired, then Purves' Statistics book will work.
The homework problems in Devore's book are of moderate difficulty but the explanation isn't any more detailed than that of a high school level statistics course (with the exception of continuous random variables). The book has some computer examples but does not discuss uses of computing packages like Matlab, R/S-plus, SAS, etc.
Unless the textbook is required for the class, for reference purposes try other textbooks for your dollars.
Rating: 
Summary: Exemplary math textbook
Review: This is very clear representation of probability and statistics. It has all the necessary formal definitions but also good explanations how those thing relate to real problems. Book has also enough examples to show how to apply things. There's also lot of exercises and end of the book there's answers to odd numbered exercises, so those exercises are not worthles as they are in many math books when there's no right answers available. Only negative thing about this book is that it doesn't show proofs to all theories. Also it doesn't use matrix and vector notations, and this is the reason why i gave just four stars. Maybe writer has thought that people reading this book are not familiar with matrix algebra, but I think that ie. regression is much easier to understand with matrices.
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