I wish I had this when I was taking my probability courses. It presents concepts in a clear and understandable way, and the solved problems provide excellent guidance. After working through the solved examples, I finally had a better understanding of random variables, pdfs, cdfs, random processes, etc. I would strongly encourage solving as many problems as you can in this book as you are going through other texts or taking a class on this. Reading through a textbook may lull you into thinking you already understand it, and waiting a long time for feedback on homework may make you more lost in class. Doing exercises will help identify your weaknesses and provide instant feedback on areas you may need to study more. With this stronger foundation, you can appreciate and understand better what the other texts are discussing.

This book is a GOD SEND. I have been utterly confused in my upper division probability course, but this book has so many great worked out problems that it worked out all my problems understanding the subject material. I thought I would fail the class, but I will probably get a B!

I used this book in conjunction with "Probability and Random Processes with Applications to Signal Processing" by Stark & Woods, and I would have to say that this Schaum's outline filled in the gaps nicely. Stark & Woods has a nice selection of exercises, but unfortunately there are no solutions to any of the problems in the book, so you have no way of knowing whether or not you have grasped the material. That is where this outline came in handy. It manages to cover all of the issues in random processes, including basic probability, random variables and multiple random variables, functions of random variables, convolution, estimation and decision theory, and queueing theory. Chapters five and six on the processing and analysis of random processes are particularly useful to those readers who are interested in applications to signal processing and communications theory. Each chapter has an excellent selection of exercises with solutions to test your knowledge. The only possible drawback of this text is that it often approaches the material from a mathematician's viewpoint more than that of an engineer. Therefore, there are quite a few proofs included as exercises that probably won't be that helpful for students of the applied sciences. The reader should already be comfortable with multivariable calculus as well as linear algebra to get the most from this book. Also, though chapter one reviews probability quite well, this should probably not be your first excursion into the subject. The only difficult part of random processes that I found this book a bit weak on was on the subject of functions of random variables. Again, this is probably because this text takes more of a mathematician's point of view and functions of random variables is more of an engineering subject.

This book has many exercises with answers/solutions to each and every exercise covering a wide range of topics from probability. The book, however, should be used along with an appropriate probability textbook. An excellent companion to Hsu's book is the introductory text by Henk Tijms. This book contains many worked-out examples and exercises as well, but also explains why probability works and how it can be applied in practice. As engineering student, I learned a lot by using both books.

I love this book's great collection of solved examples and problem exercises. It will definitely improve your understanding and clear out a lot of doubts. I would not recommend it to be used as a sole textbook. There is simply not enough theoratical information. It is definitely a very good supplement to any classic text on probability and stochastics.