Rating: 
Summary: Best Stats Book I've Read
Review: Being a non-math or stats major, I found this book to be fair and sufficient in its explanations and requirements. The other stats books I've seen have been overly difficult with unreasonably difficult problems that were never even touched upon in the examples. This book is for engineers and science majors, so I expected REAL examples and not just proofs and theorems that most of us engineers can't stand. One of the few textbooks that I won't use as a bedtime story and that's the best compliment you can give to a textbook.
Rating: 
Summary: Terribly written
Review: I would not recommend this book for anyone who actually needs to understand the concepts of probability and statistics. The notation is bad and most exercises are tedious and add little insight. Instead, I would recommend Milton and Arnold's book (which is a bit outdated, but wonderfully written) for any serious stats student. I gave this book two stars (I think I may be acting a little overgenerous) because it has a nice list of tables of distribution functions in the back and because of the abundance of exercises, some of which are worth working through.
Rating: 
Summary: This book is a no no
Review: I'm an engineering student using this book now and i find it is useless. The examples dont flow smoothly for people who have never seen this stuff before, and the reading is unbelievably dry and confusing.
Rating:
Summary: I had to get a second textbook for this class...
Review: I'm only on chapter 3, to be fair, but so far I've hated this book. I dumped $120 into it and the example problems are way too simple, and nothing like the actual exercises I'm being graded on. The sections and explanations are short, variables aren't explained well, a lot of assumptions are made. I just finished calculus 1/2/3 with the excellent Stewart book, to then go to this one is a real nightmare. Luckily for me, I've got another book on statistics and probability from a past class, and between the two of them, I can puzzle out much of it. NOT recommended.
Rating:
Summary: I had to get a second textbook for this class...
Review: I'm only on chapter 3, to be fair, but so far I've hated this book. I dumped $120 into it and the example problems are way too simple, and nothing like the actual exercises I'm being graded on. The sections and explanations are short, variables aren't explained well, a lot of assumptions are made. I just finished calculus 1/2/3 with the excellent Stewart book, to then go to this one is a real nightmare. Luckily for me, I've got another book on statistics and probability from a past class, and between the two of them, I can puzzle out much of it. NOT recommended.
Rating:
Summary: Not worth it
Review: If you are trying to learn probability, don't use this book. The examples presented in each section are pretty simple and then you get to the problems at the end of the section and they're totally out of left field. You need a second reference just to do the problems in the book. I didn't care much for prob/stats before and this book does not improve my opinion.
Rating:
Summary: Not worth the money
Review: This book is nowhere near as rigorous as most college statistics classes will be, and serves little purpose. It has many problems (a plus), but the subjects are not treated as in-depth as they should be. This is fine, I suppose, for a basic understanding of probability and statistics, but for readers who want to go beyond that, this is not worth the money. Buy DeGroot instead, it's much better.
Rating:
Summary: Confusing presentation
Review: This book presents many things in rather strange ways. For instance, the central concept of a probability distribution appears in a number of different "versions" which are likely to confuse beginners (distributions on the sample space, distributions of a random variable defined on the sample space, and distributions of functions of random variables (statistics) are discussed as if they were separate concepts). More than once the order in which the material is discussed is truly amazing. For example, the central limit theorem is discussed before the linearity property of the expectation is even mentioned, although the latter is an essential part of formulating the CLT. Many further examples could be listed here.
I do give the book credit for its effort of illustrating the material with real-world data sets. However, too little background (What exactly is measured? What is the context? Which results could be expected here?) is given in most cases, resulting in examples that convey little information beyond a sequence of numbers. In this sense I doubt the data sets are as instructive as the author claims them to be. I do not recommend this book.
Rating:
Summary: Too Wordy, Too Expensive
Review: This is a pretty unhelpful textbook.Here is part of a typical problem from this book (pg. 83):
"Construct a normal probability plot for the following sample of observations on coating thickness of low-viscosity paint ("Achieving a Target Value for a Manufacturing Process: A Case Study," J. of Quality Technology, 1992: 22-26)...
Does the author really think any student will care about the source of the data and go look it up? If he really felt the need to include citations, they should have been in the back, or better yet, online. The author could have just written "Construct a normal probability plot for the following sample:". It's an utter waste of paper (and of students' money) to create such a wordy textbook. It's ok when some problems and examples are from the "Real World", but this book insists on doing that for literally EVERY SINGLE ONE. The lack of conciseness makes the book very difficult to study from. Another pet peeve I have with this book is that while the author does put blue rectangles around key formulas and information to highlight them, the variable definitions are not included in the rectangles. So you have to go back and pore through the previous paragraphs to figure out what the variables in the formulas are!
Finally, too many of the sample problems are, as another reviewer put it, "out of left field". They don't flow from the examples or are just worded in a very confusing way. I didn't have the heart to give this one star, because clearly a lot of hard work went into creating such an impressive-looking tome. I can keep it on my bookshelf, and my friends can come over and be impressed by what a sophisticated textbook I have. However, I'm afraid the author is less interested in teaching than in merely putting his erudition on display. I hope you don't get stuck in a class with this book!
Rating:
Summary: Too Wordy, Too Expensive
Review: This is a pretty unhelpful textbook. Here is part of a typical problem from this book (pg. 83):
"Construct a normal probability plot for the following sample of observations on coating thickness of low-viscosity paint ("Achieving a Target Value for a Manufacturing Process: A Case Study," J. of Quality Technology, 1992: 22-26)...
Does the author really think any student will care about the source of the data and go look it up? If he really felt the need to include citations, they should have been in the back, or better yet, online. The author could have just written "Construct a normal probability plot for the following sample:". It's an utter waste of paper (and of students' money) to create such a wordy textbook. It's ok when some problems and examples are from the "Real World", but this book insists on doing that for literally EVERY SINGLE ONE. The lack of conciseness makes the book very difficult to study from. Another pet peeve I have with this book is that while the author does put blue rectangles around key formulas and information to highlight them, the variable definitions are not included in the rectangles. So you have to go back and pore through the previous paragraphs to figure out what the variables in the formulas are!
Finally, too many of the sample problems are, as another reviewer put it, "out of left field". They don't flow from the examples or are just worded in a very confusing way. I didn't have the heart to give this one star, because clearly a lot of hard work went into creating such an impressive-looking tome. I can keep it on my bookshelf, and my friends can come over and be impressed by what a sophisticated textbook I have. However, I'm afraid the author is less interested in teaching than in merely putting his erudition on display. I hope you don't get stuck in a class with this book!
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