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This text focuses on the utility of probability in solving real-world problems for students in a one-semester calculus-based probability course. Theory is developed to a practical degree and grounded in discussion of its practical uses in solving real-world problems. Numerous applications using up-to-date real data in engineering and the life, social, and physical sciences illustrate and motivate the many ways probability affects our lives. The text's accessible presentation carefully progresses from routine to more difficult problems to suit students of different backgrounds, and carefully explains how and where to apply methods. Students going on to more advanced courses in probability and statistics will gain a solid background in fundamental concepts and theory, while students who must apply probability to their courses engineering and the sciences will develop a working knowledge of the subject and appreciation of its practical power.
- Sales Rank: #748705 in Books
- Brand: Brand: Cengage Learning
- Published on: 2009-08-21
- Original language: English
- Number of items: 1
- Dimensions: 9.50" h x 7.75" w x .75" l, 1.95 pounds
- Binding: Hardcover
- 480 pages
- Used Book in Good Condition
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From the Back Cover
This book introduces readers to the ways probability is applied to practical problems in science, business, and engineering. The author includes interesting examples that show applications of probability theory in all these fields. The emphasis throughout is on modeling and interpretation of data rather than of abstract mathematics, stressing uses of the computer for analysis.
About the Author
Richard L. Scheaffer, Professor Emeritus of Statistics, University of Florida, received his Ph.D. in statistics from Florida State University. Accompanying a career of teaching, research and administration, Dr. Scheaffer has led efforts on the improvement of statistics education throughout the school and college curriculum. Co-author of five textbooks, he was one of the developers of the Quantitative Literacy Project that formed the basis of the data analysis strand in the curriculum standards of the National Council of Teachers of Mathematics. He also led the task force that developed the AP Statistics Program, for which he served as Chief Faculty Consultant. Dr. Scheaffer is a Fellow and past president of the American Statistical Association, a past chair of the Conference Board of the Mathematical Sciences, and an advisor on numerous statistics education projects.
Linda J. Young, Ph.D., Oklahoma State University, is a Professor of Statistics at the University of Florida where she teaches, consults, and conducts research on statistical methods in public health, agricultural, environmental, and ecological settings. Dr. Young previously was a faculty member at Oklahoma State University and the University of Nebraska. Her more than 100 publications have appeared in 49 different journals, and was a recipient of the American Statistical Association's Founders Award. She has been editor of the Journal of Agricultural, Biological and Environmental Statistics and associate editor for Biometrics and Sequential Analysis. She has served as President of the Eastern North American Region of the American Statistical Association, Vice-President of the American Statistical Association, Chair of the Committee of Presidents of Statistical Societies, member of the National Institute of Statistical Science's Board of Directors, fellow of the American Statistical Association, and elected member of the International Statistical Institute. She has also served on numerous panels for the National Science Foundation and Environmental Protection Agency. Dr. Young's recent research has focused on linking disparate data sets and the subsequent analysis of these data using spatial statistical methods.
Most helpful customer reviews
3 of 3 people found the following review helpful.
Good explanations, but needs corrections and additions.
By AmazonShopper
3.5/5 stars
First off, this book does a very good job of explaining probability concepts. Examples are explained well enough and are presented in a step by step fashion so it's not particularly hard to follow along. You'll very rarely find huge paragraphs of text, which is great if you're an engineer but bad if you're a math major. I'm docking 1/2 star because this book sometimes doesn't give enough information about a concept and how it's useful/how can it be proved.
The real reason why this book deserves 1 full star lost though is the exercises. The solutions in the back of the book are *terrible*. Not only are the "answers" incorrect, but in some cases the question would have 4 parts, but the answer would only have 3 parts. It's as though no one even bothered to cross check the questions and answers before putting this to print? I'd forgive them if this was 1 or 2 scattered problems, but it really ended up being every other problem with a mistake, in every chapter. It's extremely frustrating to take time trying to find a mistake you made, only to realize it's the book that made the mistake.
So, in summary,this book is a good "intro" book...probably best suited for engineers. If you want a book that goes through long proofs of various formulas, look elsewhere.
2 of 2 people found the following review helpful.
Ok, but has issues...
By ResponsibleReviews
This book was required for a class I took, but I wish the teacher had selected a different one. The material that this covers is pretty clear most of the time, but when you go to work on the homework problems watch out. As if doing probability problems is not difficult enough, some problems in this book are misleading and if you go to check your work in the back of the book you will find that for a handful of problems in each section the answer is wrong. I compared my answer with other students and the teacher to verify this. All in all this is an ok book, but it makes you second guess yourself.
0 of 0 people found the following review helpful.
Good examples, but many mistakes.
By Robbie R.
As an Electrical Engineering student currently enrolled in a probability course using this textbook, I think this book deserves three stars for the following reasons:
Negatives:
-- Many answers given at the back of the book are simply incorrect or incomplete. Often, an error in simple arithmetic will creep into the given answer for an odd problem, giving students like me an enormous headache and difficulty in comprehension. Since some answers are incorrect, I can't reliably study for exams using any problems other than examples in the book. My final in the class is in three weeks and I plan to completely avoid working anything from this text other than an example-like problem.
Positives:
-- Good conceptual explanation of the mathematical foundations of probability.
-- Relevant and usually complete examples.
-- The cover art is nice.
Reasons in Limbo:
-- The examples are good for engineering majors, simply presented with very few paragraph-style proofs obfuscating the concepts. On the other hand, in my Theory of Probability class, sometimes a more complete proof than is provided is necessary on my exams. Usually it's not too much of a stretch to expand a given proof when needed.
Taking it all into consideration, I'm giving this book 3 stars, largely as a warning that many answers in the back are completely incorrect.
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