Rating: 
Summary: What a terrible book
Review: I am a graduate student using this book in a class. I would really like to warn other people from using it.The book describes everything with a lot of examples. As a result of this you do not get a basic understanding, but rather some examples that you can adapt and use for a problem that you have to solve. It is like learning that a wheel is turning because you might turn it with your hand, rather than because you are applying a torque to it. Or that a lamp is turned on because you might hit the switch, rather than because a current flows through it. For some reason everything has to be described with CDFs instead of PDFs in the book. It seems like PDFs are something that is difficult to imagine for the author. I once had a teacher in a class, and a book containing a lot of examples like this one. He claimed that he could write everything the book contained on 2 pages - He was right!! I think the same thing could be done with this book. Do not choose this book. It is highly unrecommended.
Rating: 
Summary: Please dont do this to your students.
Review: I am a senior in Computer Science and this book was used as a text book for our Probability class. Our class was very unhappy with it. The author is a very intelligent person, but our class had a hard time keeping up with him. Many of the complex problems refer to equations, tables, and more importantly previous problems that had been touched briefly on 20 or more pages previously. All of the tables were given only once and in a few cases, Chapter 5 problems have you flipping back to Chapter 3 just to read a table. This meant we were constantly flipping pages back and forth to try and read the material. There were also errors in the book that I couldn't believe hadn't been caught by now. Many of the errors are difficult to catch as a student because they fall in equation definitions that are only given once. One error had a double integral misdefined. The author also assumes that the students can identify Taylor series expansions, geometric, and e^x by solving discrete summations, which to be honest I would have appreciated the author going thru at least one example, or giving the student some tips on identifying these. The notation in this book is also confusing. Many of the problems deal with finding the double integral of a function that invloves 'x' and 'y' yet the author uses X and Y to denote a random variable from the respective functions, therefore the book is riddled with equations that sometimes have x, X, and x' all meaning completely different things. This was extremely confusing once we started doing joint probabilites that involved y,Y,y',x,X,x'. Also the author introduces <x> to define the mean, but he doesn't explain this is a defintion but instead introduces it in chapter one problem 7 and asks the student to prove the discrete summation, which I won't try and convey here. In my opinion this book is too difficult for undergraduate classes, but perhaps it would suit graduate level students, if the errors were corrected, the notation was cleaned up, and a few more examples were given.
Rating: 
Summary: Used in Graduate Class on Probability and Random Processes
Review: I used this book for a graduate class in Probaility and Random Processes and we covered every chapter. I gave the book three stars based on other probability books I have used, but compared to other engineering books I would rate it lower. I feel main problem with the book is the examples not very helpful in solving the 100+ problems that accompany each chapter. Most of the examples were just useless explanations graphs. The book also seems to gloss over some of the important concepts needed to solve the homework problems. The only homework problems that I found useful were the MATLAB examples. I would recommend doing these problems even if they are not assigned. The book also does a poor job covering applications, especially in the later chapters on random processes. I would have been interested in more signal processing and communications applications, the main reason I took a course on probability and random processes. As far a background for a person using this book, I would recommend the person be graduate student with a solid math background.
Rating:
Summary: Useful, non-rigorous reference
Review: I used this book in a sophomore-level probability course for electrical engineers and I found the book a bit confusing at the time. The notation is somewhat awkward and examples are interleaved throughout general concepts, making it difficult to discern key ideas. During my doctoral studies, I gained a different perspective. I consistently found the book to be a valuable starting point for many concepts and I now find the examples a quick way to brush up on elementary principles. However, Leon-Garcia doesn't give a thorough approach to probability theory (there are essentially no theorems) and avoids set theory almost entirely. To really put my teeth into something, I would have to track down a more advanced text for any particular concept I was interested in. Basically, Leon-Garcia tries to seperate "Probability and Random Processes" from rigorous mathematics.... something similar to eating fat-free cheesecake.
Rating:
Summary: so so book
Review: I used this textbook for a junior level class. Frankly, although the book is good initially, the end of chapter problems are way too hard, especially in chapters 3,4,6 and 7. Also, much of the book is formula, which is a bit too much for undergrads.
Rating: 
Summary: So helpful!
Review: It was really hard to undestand the context related to probability stuff and it is the best way to solve the many problems in order to understand. In my case, the examples of the text book were not enough. That's why I purchased this book. Absolutely, my thought was right. This book is so helpfule to understand the unclear questions related to probability. The explanation of each question give me the visualization of probability world. If you are preparing the exam, buy this.
Rating:
Summary: Good for the methematically oriented
Review: Lets face it... probability theory is based on a lot of math that one does not see in the introductory level math classes at college. This book explains a lot of the more difficult stuff well. I am not one for doing the problems at the end of the chapter. For a general overview, I found this book to be good. Not great, but good. It did most of the concept explaining through examples, and as an engineer, that suited me fine. Disclaimer - don't buy this if you don't like looking at a long formula, you will simply end up hating it.
Rating:
Summary: So helpful!
Review: Probability and Random Processes for Electrical Engineering is not a very well-written book. The book seems to be gaining more favor with EE and computer science programs, not because of the quality of the book, but rather the need to standardize on texts, regardless of the quality. The book itself is extremely sketchy and lacks mathematical rigor, perhaps because it is supposed to be meant for engineers and not for math majors, but even so it does not explain its subject very well, even though preface states that it is accessible. For example, the concept of counting theory is extremely important in probabiity, but the author devotes a total of six pages to the subject and even notes that counting theory can be skipped without loss of continuity. I don't think so! Also the author's definitions of discrete and continous sample spaces are not quite correct. There are not enough examples outlined in the book and many of the homework problems have little relevance to the examples presented. A good instructor could make something out of this book, but be sure to get a Schaum's outline for more problems and another text to complement this one.
Rating:
Summary: Not the best book available on the subject
Review: Probability and Random Processes for Electrical Engineering is not a very well-written book. The book seems to be gaining more favor with EE and computer science programs, not because of the quality of the book, but rather the need to standardize on texts, regardless of the quality. The book itself is extremely sketchy and lacks mathematical rigor, perhaps because it is supposed to be meant for engineers and not for math majors, but even so it does not explain its subject very well, even though preface states that it is accessible. For example, the concept of counting theory is extremely important in probabiity, but the author devotes a total of six pages to the subject and even notes that counting theory can be skipped without loss of continuity. I don't think so! Also the author's definitions of discrete and continous sample spaces are not quite correct. There are not enough examples outlined in the book and many of the homework problems have little relevance to the examples presented. A good instructor could make something out of this book, but be sure to get a Schaum's outline for more problems and another text to complement this one.
Rating:
Summary: Not a well-written book
Review: This book is a confusing muddle and for students who have no prior knowledge of the subject, it could not be a worse textbook. It seems as if more graduate programs in electrical and computer engineering are using this text, not because it teaches the subject well, but "to keep up with the Joneses," so to speak. There are too few examples to illustrate problems, and many of the homework exercises are not well explained and have no relevance to the text. The text itself is too bare bones. The introduction uses the words easily accessible or similar terms to describe the book, but that is not true. In the hands of a good lecturer/professor, it may be worthwhile but if you are taking a class with a bad lecturer who is using this text,then you are in deep trouble! Caveat emptor!
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