ISBN0534377416

This is an adequate text up until chapter 6. The probability chapter the the discrete probability distributions are great. The concepts and derivations are logically laid out and make sense. Things begin to get frustrating in chapter 4 and really fall apart after chapter 6. After chapter four the author no longer tries to put anything in context. He derives very little and simply states long, cryptic formulas and expects the reader to magicaly understand the big picture and fill in the gaps on their own. He skips over the over 200 years of the development in statictical theory and simply states the results and the student is expected to fill in the gap. The most self evident properties are expounded on in the chapters and the most important and subtle properties are hidden in the exercises or neglected altogether. I am nearly finished with my undergraduate degree in applied mathematics and am mathematicaly mature. I am comfortable with both applied and pure/proof-type mathematics and this text makes my stomach turn. It makes me want to reconsider my major. I am giving this text 2 stars simply because the first 5 chapters are adequate. If you just need a course in probability, this might be the text for you. If you need to move on to statistical inference and you need the big picture/contextual background explained rather than pluging and chuging blindly with nonsensical formulas, then this is not the text for you. Way to drop the ball, Wackerly!

This book has good explanations of the topics covered in each section , but the solutions to the odd numbered problems are full of errors. I can't stand this book anymore , I need to check my solutions to reinforce my knowledge and the book doesn't provide correct solutions.

I would recommend to everyone to stay away from this book.

Mathematical Statistics with Applications
by William Mendenhall and other authors is a higher level university text on probability and statistics, dealing with some of the underlying mathematics and calculus, moments, probability generation functions and all that sort of thing.

Definitely not your light right type of mathematics books by any stretch of the imaginaiton.

The text isn't "bad," but I would look elsewhere. Sections and exercises are numbered in an uncomfortable way. Important topics and formulae are hidden within dense paragraphs, instead of being visually offset. The overall graphic and textual communication works... barely. There is much room for improvement.

I had to use this text for my Stat Theory classes. This book is very frustrating in that it fails to mention some very useful theorems. Example: A problem from Ch. 3 asks: If Y is a random variable with moment-generating function m(t), and if W is given by W = aY + b, show that the m.g.f. of W is e^(tb)*m(at). In the section containing this problem, two theorems are omitted, one of which states that if X and Y are indep. random variables having m.g.f.'s Mx(t) and My(t), respectively, then Mx+y(t) = Mx(t)*My(t).

Would have been nice to know this while trying to write the proof since one might not know this theorem and assume that Mx+y(t) = Mx(t) + My(t). You run into this situation again and again in this book, whereas you can buy a Schaum's Outline of Probability and Statistics for about 1/6th the price and it has this theorem. If you need to buy this book, I recommend Schaum's which also has a lot more worked problems to study. This book is another example of old professors writing a bad text to make themselves feel smarter than students who are 30 years younger then them and can't rediscover well-known theorems in their spare time.