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Probability, Random Variables and Stochastic Processes 4th Edition
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Top Customer Reviews
The treatment has no measure theory, cuts to the chase, and can be used as a desk reference. If you want measure theory, go spend some time reading Billingsley. A deep understanding of measure theory is not necessary for scientific and engineering applications; it is not necessary for those who do not want to work on theorems and technical proofs.
I've notice a few complaints in the comments section by people who felt frustrated by the treatment: do not pay attention to them. Ignore them. It the subject itself that is difficult, not this book. The book, in fact, is admirable and comprehensive given the current state of the art.
I am using this book as a benchmark while writing my own, but more advanced, textbook (on errors in use of statistical models). Anything derived and presented in Papoulis, I can skip. And when students ask me what they need as pre-requisite to attend my class or read my book, my answer is: Papoulis if you are a scientist, Varadhan if you are more abstract.
1. My instructor re-ordered some of the content of the text for his course. It seemed necessary to understand certain concepts.
2. As one of the previous reviews mentioned, some of the important aspects of probability theory were hidden in problems, these were brought out by the instructor either as homeworks or as part of lecture notes and explained. This also means that it is not enough to just read this text and understand the examples. It is almost as important to go through the problems to get the complete picture
3. All in all I liked the book but I sure would not have liked it as much if I did not have a good instructor to go with it. Definitely not a self-study book.
For example, the material on power spectra is of more than academic interest and is useful in applications; the bivariate Taylor expansion for moments of a function of two distributions has been used again and again in applications in industry; especially in the analysis of the ratio of noisy variables arising from radar measurements. The point is that the text provides the material in a readily accessible way for someone who needs it in the "real world" of engineering analysis.
One good feature of this book (and maybe this is why it's so widely used) is that it covers a very extensive list of topics.
I'm really surprised by the negative reviews of this book. If these complaints come from undergraduates, I can sympathize a bit. This is definitely a graduate-level book, and I think it is a mistake to use in in an undergrad course. On the other hand, I can't sympathize with such complaints if they from grad students. The complaint seems to be that it doesn't make the subject "easy"; unfortunately, there is nothing "easy" about stochastic processes. Some things in life require effort and commitment.
Most Recent Customer Reviews
This book is not for the uninitiated in random variables. This book serves best as a reference, and even in that endeavor it could be better. Read morePublished 1 month ago by DejaEntendrew
Good luck learning from this book, it's intended for a graduate program but is so dry that the only people who use it are proffesors who do nothing but theory and math. Read morePublished 2 months ago by Vladimir Khodus
Good Textbook with bunch of problems and covering various topics.Published 10 months ago by Ahmed Morsy
I have studied probability and stochastic processes in undergraduate mathematics, for a brief stint as an actuary and in graduate school for electrical engineering. Read morePublished 13 months ago by reviewbot9000