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Schaum's Outline of Probability, Random Variables, and Random Processes, Second Edition (Schaum's Outline Series) [Paperback]

Hwei P Hsu
4.8 out of 5 stars  See all reviews (4 customer reviews)

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Schaum's Outline of Probability, Random Variables, and Random Processes, 3rd Edition (Schaum's Outline Series) Schaum's Outline of Probability, Random Variables, and Random Processes, 3rd Edition (Schaum's Outline Series)
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Book Description

1 Sep 2010 0071632891 978-0071632898 2

Study faster, learn better, and get top grades

Modified to conform to the current curriculum, Schaum's Outline of Probability, Random Variables, and Random Processes complements these courses in scope and sequence to help you understand its basic concepts. The book offers extra practice on topics such as bivariate random variables, joint distribution functions, moment generating functions, Poisson processes, Wiener processes, power spectral densities, and white noise. You'll also get coverage of linear systems to random outputs, Fourier series and Karhunen-Loéve expansions, Fourier transform of random processes, parameter estimation, Bayes' estimation, and mean square estimation. Appropriate for the following courses: Probability, Random Processes, Stochastic Processes, Probability and Random Variables, Introduction to Probability and Statistics

Features:

  • 405 solved problems
  • Additional material on distributions, the Markov Process, and Martingales
  • Support for all the major textbooks for probability, variables, and processes courses

Topics include: Probability, Random Variables, Multiple Random Variables, Functions of Random Variables, Expectation, Limit Theorems, Random Processes, Analysis and Processing of Random Processes, Estimation Theory, Decision Theory, Queueing Theory



Product details

  • Paperback: 432 pages
  • Publisher: Schaum's Outlines; 2 edition (1 Sep 2010)
  • Language: English
  • ISBN-10: 0071632891
  • ISBN-13: 978-0071632898
  • Product Dimensions: 8.1 x 10.7 x 0.8 cm
  • Average Customer Review: 4.8 out of 5 stars  See all reviews (4 customer reviews)
  • Amazon Bestsellers Rank: 348,939 in Books (See Top 100 in Books)
  • See Complete Table of Contents

Product Description

About the Author

Hwei P. Hsu was Professor of Electrical Engineering at Fairleigh Dickinson University. He received his B.S. from National Taiwan University and M.S. and Ph.D. from Case Institute of Technology. He has published several books which include Schaum's Outline of Analog and Digital Communications and Schaum's Outline of Signals and Systems.


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Front Cover | Copyright | Table of Contents | Excerpt | Index
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Customer Reviews

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Most Helpful Customer Reviews
1 of 1 people found the following review helpful
4.0 out of 5 stars Good for undergraduate studies 27 Feb 2013
Format:Paperback|Verified Purchase
In general, i can say that i liked it. It is well written and easily understood. Good for undergraduate studies, suitable for engineers (say mechanical & electrical), not suitable for mathematicians.
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5.0 out of 5 stars Great book 18 May 2013
By chris
Format:Paperback|Verified Purchase
Like all the books in this series, it has an excellent range of worked examples. Many other books on this topic are mathematically rigorous, but contain little in the way of example material that is needed to fully grasp the application of the topic. This is one of the most accessible books on the topic I have encountered to date.
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5.0 out of 5 stars Very well structured overview 22 July 2012
Format:Paperback|Verified Purchase
This book is rather short on explanation, but it is very well structured, the topics covered and the worked examples are well chosen to build up a coherent and useful overview over this important topic. My copy was also remarkably cheap for such a well put together text! Highly recommended.
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2 of 3 people found the following review helpful
Format:Paperback
If like me you have no prior maths experience whatsoever and want to be able to read and understand some of the more advanced under-grad/grad text's on Prob/Random Variables and Stochastic Processes then this book is ideal.. The subject is taught in a concise manner from the ground up assuming very little or no prior knowledge..there are plenty of worked examples which help glide you through your learning.. As suggested in other reviews, use this book alone first or as a companion text to understanding books such as [Probability, Random Variables and Stochastic Processes - Athanasios Papoulis;] Again, I went from no knowledge to undergraduate level in about 3 weeks (and I'm really stupid).. Enjoy!!
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Most Helpful Customer Reviews on Amazon.com (beta)
Amazon.com: 4.6 out of 5 stars  17 reviews
3 of 3 people found the following review helpful
5.0 out of 5 stars NIcely organized, fast, and clear 10 Aug 2013
By Tim Jones - Published on Amazon.com
Format:Paperback|Verified Purchase
If you need to teach an undergraduate statistics class, such as Statistics for Engineers and Scientists, this is the book to prepare with. Such books as Devore and Johnson's "Statistics with Calculus" texts use minimal calculus. This book in contrast uses it extensively, but at a first year (through multi-variable) level. The best combination of textbooks is possible: use Devore or Johnson as a basis, and, as student's are able and willing take problems and classroom exposition from Hsu's PRV&RP.

A good argument could be made that in terms of evolving mathematical thinking -- definitions and theorems yielding analysis of applications and problems -- Hsu is far superior. He is quick and tight. On the other hand, sophomore students might not be able to get a more sophisticated mathematical exposition. That's where Devore and Johnson come in. Their texts also present the usual histograms, dot-plots, stem and leaf etc. level stuff of elementary statistics. They don't, however, take the use of calculus far enough. Somewhere in-between is the ideal. If you can get students up to Hsu then you've done a good job teaching.

The only slight catch with Hsu's book is that it stresses electrical and computer engineering over other types -- civil and mechanical. Some distributions that are in Devore and Johnson are not in Hsu and vice-versa. That said the core distributions (normal and binomial) are succinctly covered with as much calculus as is possible for a student having taken or in the process of taking a full two or three term calculus sequence.
1 of 1 people found the following review helpful
5.0 out of 5 stars Far better than my text book. 22 Dec 2013
By Emrys E. Maier - Published on Amazon.com
Format:Paperback|Verified Purchase
My professor and my text book were very difficult to follow so I bought this outline for help. I'm fairly certain this is what got my the A in probability -- without this outline I would have been entirely lost last semester!
1 of 1 people found the following review helpful
4.0 out of 5 stars Useful as a Companion to an Engineering Stats Course 17 April 2013
By Matt - Published on Amazon.com
Format:Paperback|Verified Purchase
I like the concise nature of the topics. They are explained fairly well for use as a companion to a full course. I do find some steps are skipped for simplicity reasons and conciseness which can be a but frustrating for new and confusing topics. The solved problems at the end of each chapter are the most beneficial to learning....
1 of 1 people found the following review helpful
5.0 out of 5 stars concise and clear 19 Feb 2013
By Flatfive - Published on Amazon.com
Format:Paperback|Verified Purchase
I've only worked through parts of chapter 5 (random
processes) so far, but I've found the treatment here
clearer than other books I've used. The presentation
is concise, with good notation and short but very
helpful commentary.

Also, the author picked a nice level of rigor. For
example, the notion of sigma algebra is introduced
right at the beginning of the book, but with a light
touch on notation and use of white space.
1 of 1 people found the following review helpful
5.0 out of 5 stars Just fantastic 21 Nov 2012
By endbegin - Published on Amazon.com
Format:Paperback
This book is an excellent way to self-learn what can be difficult topic. Each chapter has a brief theoretical introduction to the concepts followed by numerous solved problems, in a progressively increasing order of difficulty. Even though the subject matter can be difficult to absorb at times, and you need a fair level of mathematical maturity before you can tackle it, this book does a great job of breaking things down in an easier to digest format. It covers most of the well-known theorems and problems in this field, both from a mathematical and an applied perspective. I wouldn't have made it through my graduate studies without its help, and recommend it highly.
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