Introduction to Probability and Statistics: Principles and Applications for Engineering and the Computing Sciences [Hardcover]

J. Susan Milton (Author), Jesse Arnold (Author)

Book Description

Publication Date: September 30, 2002 | ISBN-10: 007246836X | ISBN-13: 978-0072468366 | Edition: 4

This well-respected text is designed for the first course in probability and statistics taken by students majoring in Engineering and the Computing Sciences. The prerequisite is one year of calculus. The text offers a balanced presentation of applications and theory. The authors take care to develop the theoretical foundations for the statistical methods presented at a level that is accessible to students with only a calculus background. They explore the practical implications of the formal results to problem-solving so students gain an understanding of the logic behind the techniques as well as practice in using them. The examples, exercises, and applications were chosen specifically for students in engineering and computer science and include opportunities for real data analysis.

Product Details

• Hardcover: 816 pages
• Publisher: McGraw-Hill Science/Engineering/Math; 4 edition (September 30, 2002)
• Language: English
• ISBN-10: 007246836X
• ISBN-13: 978-0072468366
• Product Dimensions: 9.5 x 6.6 x 1.4 inches
• Shipping Weight: 2.6 pounds (View shipping rates and policies)
• Average Customer Review: 3.2 out of 5 stars  See all reviews (13 customer reviews)
• Amazon Best Sellers Rank: #254,250 in Books (See Top 100 in Books)

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Customer Reviews

Most Helpful Customer Reviews

8 of 8 people found the following review helpful:

2.0 out of 5 stars a standard statistics book for engineers, May 18, 2007

By 

Stanislav Kolenikov (Columbia, MO, United States; Moscow, Russia) - See all my reviews
(REAL NAME)   

This review is from: Introduction to Probability and Statistics: Principles and Applications for Engineering and the Computing Sciences (Hardcover)

I taught a class at upper undergraduate level (mostly junior students) for a non-majors (mostly engineering students, some economics and political science) at a research university using this book.

It was written in the mid 1980s, and has not seen major updates even though it now comes in 4th edition. One of the assignments I gave was to comment whether you recognize the brand names of the mainframe computers mentioned in the problem. Newer stuff like say the bootstrap or machine learning or anything like that is not mentioned anywhere nearly. True, it has all the major results and techniques, but it was written by statisticians as the first course in statistics for to-be-statisticians, rather than the-only-course-in-statistics-you'll-ever-see for engineers. Thus a lot of things could have been presented in a different way with a different depth of exposure. Say the reliability, arguably a more important topic for engineers than moment generating function techniques, deserves a whole separate chapter, rather than being stuck in a middle of the chapter on continuous distributions. Simulations could have been highlighted throughout the book -- a good fraction of my students would probably be geekier than me with computers. I would unite all the confidence intervals under the umbrella of a single chapter, rather than presenting the CI for mean in one chapter and CI for variance in the next one. And so on. There even were errors in the answers in the end of the book, although you would probably expect the fourth edition not to have any.

Students complained a lot about the book in my class, too. Some said it did not help much, although there were others who did not come much to class (admittedly, I am a pretty boring lecturer) and got B's and A's, so apparently it was of some use to them. The price is of course also an issue: I personally won't pay $120 for book of this quality to sit in my professional library, and it sucks that I have my students buy it.

[Wasserman's [ASIN:0387402721 All of Statistics: A Concise Course in Statistical Inference (Springer Texts in Statistics)]] is a much more modern book, although in all likelihood it would be difficult for my clientelle. My other favorite is Utts' Seeing Through Statistics (with CD-ROM and InfoTrac ), but this one is on the other side of technicality, being too easy. Finally, for engineering students specifically, Ryan's Modern Engineering Statistics (Hardcover) appears to be a much better text, although I have not taught from it, and my recommendation is based on just browsing through the pages and supplementing the current book with examples and problems from Ryan's book.

10 of 12 people found the following review helpful:

1.0 out of 5 stars This book made me hate statistics., November 30, 2002

By 

Student at Virginia Tech (Herndon, VA USA) - See all my reviews

This review is from: Introduction to Probability and Statistics: Principles and Applications for Engineering and the Computing Sciences (The McGraw-Hill series in probability & statistics) (Hardcover)

I'm a math/computer science major taking a stat course at virginia tech and the professor is using this horrible book. Reading it is pure drudgery. It is bland, boring, wordy, and hideously difficult to extract any real information from. It seems to assume the student already knows everything about statistics, as it's examples and explanations are so convoluted, lengthy, and conceptually incoherent that any attempt to follow them is a waste of time. The exercises (at least the ones my professor assigns) infallibly require a ridiculous amount of numerical computation that takes forever to enter by hand, like finding the mean of 60-80 sample points. This book made me hate statistics which is a shame because it is a beautiful and highly applicable field. If you are forced to use this text then do whatever you can to learn the material from an outside source, be it another text, a friend, the internet, anything but the book.

1 of 1 people found the following review helpful:

4.0 out of 5 stars Very Good as Textbook, July 14, 2005

By 

TTHT - See all my reviews

This review is from: Introduction to Probability and Statistics: Principles and Applications for Engineering and the Computing Sciences (Hardcover)

This book was recently used as a textbook for an engineering statistics class. Many of the students liked the book and found it easy to read. The level of mathematics in the book is excellent for a college level statistics textbook. I would have given it a five star rating if propogation of error and nonlinear regression analysis were covered in the textbook.