Intuitive Probability and Random Processes using MATLAB: Steven Kay

Intuitive Probability and Random Processes using MATLAB: Steven Kay Summary:

Springer | ISBN: 0387241574 | 2005-11-16 | PDF (OCR) | 833 pages | 51.3 Mb

Intuitive Probability and Random Processes using MATLAB is an introduction to probability and random processes that merges theory with practice. Based on the author's belief that only "hands-on" experience with the material can promote intuitive understanding, the approach is to motivate the need for theory using MATLAB examples, followed by theory and analysis, and finally descriptions of "real-world" examples to acquaint the reader with a wide variety of applications. The latter is intended to answer the usual question "Why do we have to study this?" Other salient features are: *heavy reliance on computer simulation for illustration and student exercises *the incorporation of MATLAB programs and code segments *discussion of discrete random variables followed by continuous random variables to minimize confusion *summary sections at the beginning of each chapter *in-line equation explanations *warnings on common errors and pitfalls *over 750 problems designed to help the reader assimilate and extend the concepts Intuitive Probability and Random Processes using MATLAB is intended for undergraduate and first-year graduate students in engineering. The practicing engineer as well as others having the appropriate mathematical background will also benefit from this book. About the Author Steven M. Kay is a Professor of Electrical Engineering at the University of Rhode Island and a leading expert in signal processing. He has received the Education Award "for outstanding contributions in education and in writing scholarly books and texts..." from the IEEE Signal Processing society and has been listed as among the 250 most cited researchers in the world in engineering.

Summary: More bang for your buck

Rating: 4

Here's what you need to know about this book: 1. Don't be confused about the title. By "intuitive" he means he's not going into theoretical measure theory stuff. The material here is standard material, found on many books.

2. The explanations are very clear, doesn't hold back on formalism (to the extent it's possible to be formal - meaning, he's not sloppy about his presentation), and are followed or preceded by real world examples.

3. You get to use Matlab. That is, you learn the basics of using a computer for problems that are aproximate to real world problems.

4. But just because he uses Matlab doesn't mean you don't have a lot (a lot) of traditional excercises. The computer learning is not necessary, it's a "bonus".

5. This book has over 800 pages, and has many illustrations that help a lot in understanding!

6. Later chapters go into more advanced stuff you probably won't see in your first course in probability.

So, all in all, this is an excellent purchase. The author is very talented in explaining, chooses very good examples and additionally, you get to put this stuff your learning to practice using a computer. I think all these factors make the book stand out and introduce probability in a modern way. If you're having difficulty with other shorter texts (as I was) and if you've got an itch to scratch (wants to use your computer to simulate some stuff and do some problems), I think you'll enjoy and benefit quite a lot from this book. Maybe some other books are a little more demanding on math (e.g. Ross), but it's no use if you cant' understand or if you want to become more proficient in the use of the computer for the modelling of probability problems. The real world problems will appeal more to engineering/applied math/comp sci students than other (e.g., biology students).

The criticism I have is that I would have prefered if it had used the free/open source R language/environment (but I guess since the author comes from Electrical Engineering, Matlab makes more sense). Also, I would like to have a solutions manual for *all* the exercises that's not only for teachers (this American infantile treatment of students bothers me). I would have liked more "mathy" examples such as those Ross has ("harder" examples).

Summary: Pretty good book, worth buying

Rating: 4

This is a good book, I have been reading it, so far I enjoy it. compared with other book on the same topic, this book is worth buying.

Summary: Very pedagogical exposition

Rating: 4

you will get a solid understanding of each topic/chapter title. Not only engineering but also math students should be trained in the spirit of this book. Each chapter culminates in a real world application which is indeed interesting, and not completely trivial. Few books teach the theory but also bring you to the level where you can apply this theory to problems. However, there is a drawback, in my opinion; since the book is supposed to address grad students some mathematical sophistication could be assumed so as to achieve a more concise presentation. I don't blame the author for extreme clarity of course, but usually you want to get to the interesting parts of any subject at a much higher pace. At some points one could say the book is a bit verbose. Overall, it is almost excellent taking into account its target-group (mostly ece students) and the material it deals with (elementary applied probability).

Summary: Excellent Book

Rating: 5

This is a very good book for classes and suitable for textbook. I recomend this book for who is the new in the probability. The book is readable, clear explaination and MATLAB examples are understandable.

N.A.S.

Summary: Intuitive as it says

Rating: 5

It's a great book for probability. Explain the abstract concept in an easy way. You will find out that you go through all those difficulties just by following the author. I got full point in my first quiz which was never the case for my math courses.

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