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First Course in Probability, A (8th Edition) (Hardcover)

by Sheldon Ross (Author)

Textbook Details
* Paperback: 552 pages
* Publisher: Prentice Hall; 8 edition (January 7, 2009)
* Language: English
* ISBN-10: 013603313X
* ISBN-13: 978-0136033134
* Dimensions: 10 x 8.1 x 1 inches
* Shipping Weight: 2.5 pounds
* Rating:

Textbook Description
KEY BENEFIT: A First Course in Probability, Eighth Edition, features clear and intuitive explanations of the mathematics of probability theory, outstanding problem sets, and a variety of diverse examples and applications. This book is ideal for an upper-level undergraduate or graduate level introduction to probability for math, science, engineering and business students. It assumes a background in elementary calculus.

KEY TOPICS: Combinatorial Analysis; Axioms of Probability; Conditional Probability and Independence; Random Variables; Continuous Random Variables; Jointly Distributed Random Variables; Properties of Expectation; Limit Theorems; Additional Topics in Probability; Simulation
MARKET: For all readers interested in probability and statistics.

A First Course in Probability, Fourth Edition, thoroughly presents the mathematics of probability theory as well as the many diverse applications of the subject. Fundamental concepts such as the principles of combinational analysis, key to computing probabilities, and the axioms of probability theory are thoroughly covered early on. The author’s concise writing style and refined textual organization covers topics such as conditional probability and independence of events, conditioning, expectation, and discrete, continuous, and jointly distributed random variables with unparalleled clarity. Interesting exercises and numerous worked examples solidly reinforce concepts. –This text refers to an out of print or unavailable edition of this title.

First Course in Probability Review
I used this book (as well as the SOA sample exams) as my sole means of preparation for the Actuary Examination P. Ross does an excellent job of utilizing a plethora of examples in order teach a particular concept. In some cases, a chapter may consist of two pages of instruction, followed by dozens of examples. This method tends to be extremely effective with regard to test preparation, but more frustrating for students using this as a course textbook. The proofs provided are fairly vigorous, but a strong background in Calculus is essential to understanding any significant portion of this book.
The chapter discussing “Jointly Distributed Random Variables” is the longest in the book, and perhaps rightly so, considering this comprises the majority of the P exam. However, in 50 pages of text, about five pages involves a formal discussion of terms and proofs, and the rest is made up of about 40 examples, many which span multiple pages. Again, this happens to be quite effective when paired with the SOA example questions, but may prove to be a difficult text to follow when a professor expects you to understand the finer points of probability theory.

I’ve only read the first four chapters of this book so far, but overall, I am enjoying the book. In order to give a sense of how difficult the book is (or perhaps how slow I am in picking up the material) – it sometimes takes me a full hour just to read 3 pages. Furthermore, sometimes, I have had to put the book down and reread the pages another day to be able to comprehend the material. This is with a goal of really trying to understand each page. My math background includes classes in Calculus, Linear Algebra, and Introductory Differential Equations. Each chapter has three sets of problems: chapter problems, theoretical problems, and self-test problems. The self-test problems have concise solutions that also can take a some time to understand. There are also a few typos here and there – not that many though. I would recommend this book only to those who are highly disciplined and persistent with studying math. I would also recommend finding a person knowledged in Probability for questions you’ll definitely have. For me, I’ve had to also do a lot of the problems to really understand the material. Lastly, this book has been my first introduction to probability.

I absolutely love this book. The numerous examples in it are so mathematically rich and so broadly applicable and diverse in content, that it makes my heart pound every time I read it. Granted, if you’re not a math type they will be very difficult to understand, but if you’re into math this this the book you’ve been looking for since 7th grade. The examples in every section give you a much more thorough understanding of the topic than in any other book, so you have to do little exploring yourself. Also, the examples are so general and so good that…wow!

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