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Probability: With Applications and R Hardcover – November 4, 2013

ISBN-13: 978-1118241257 ISBN-10: 1118241258 Edition: 1st

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Product Details

  • Hardcover: 520 pages
  • Publisher: Wiley; 1 edition (November 4, 2013)
  • Language: English
  • ISBN-10: 1118241258
  • ISBN-13: 978-1118241257
  • Product Dimensions: 6.4 x 1.2 x 9.6 inches
  • Shipping Weight: 1.8 pounds (View shipping rates and policies)
  • Average Customer Review: 4.6 out of 5 stars  See all reviews (17 customer reviews)
  • Amazon Best Sellers Rank: #636,875 in Books (See Top 100 in Books)

Editorial Reviews

From the Back Cover

An introduction to probability at the undergraduate level

Chance and randomness are encountered on a daily basis. Authored by a highly qualified professor in the field, Probability: With Applications and R delves into the theories and applications essential to obtaining a thorough understanding of probability.

With real-life examples and thoughtful exercises from fields as diverse as biology, computer science, cryptology, ecology, public health, and sports, the book is accessible for a variety of readers. The book's emphasis on simulation through the use of the popular R software language clarifies and illustrates key computational and theoretical results.

Probability: With Applications and R helps readers develop problem-solving skills and delivers an appropriate mix of theory and application. The book includes:

  • Chapters covering first principles, conditional probability, independent trials, random variables, discrete distributions, continuous probability, continuous distributions, conditional distribution, and limits
  • An early introduction to random variables and Monte Carlo simulation and an emphasis on conditional probability, conditioning, and developing probabilistic intuition
  • An R tutorial with example script files
  • Many classic and historical problems of probability as well as non-traditional material, such as Benford's law, power-law distributions, and Bayesian statistics
  • A topics section with suitable material for projects and explorations, such as random walk on graphs, Markov chains, and Markov chain Monte Carlo
  • Chapter-by-chapter summaries and hundreds of practical exercises

Probability: With Applications and R is an ideal text for a beginning course in probability at the undergraduate level.

About the Author

ROBERT P. DOBROW, PhD, is Professor of Mathematics at Carleton College. He has taught probability for over fifteen years and has authored numerous papers in probability theory, Markov chains, and statistics.


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Customer Reviews

It's interesting, and a good book, if you want the mathematical and statistical foundations of probability theory.
Jesse D. Walker
R is a scripting language, and the student should be familiar with at least the rudiments of computer programming before engaging with the material in this book.
Dr. Bojan Tunguz
The text is written in a clear and precise style and is chock-full of excellent examples and exercises that range from accessible to very challenging.
Miles

Most Helpful Customer Reviews

3 of 3 people found the following review helpful By Jesse D. Walker on March 4, 2014
Format: Hardcover Vine Customer Review of Free Product ( What's this? )
As statistics books go, this one's actually readable. As a doctoral candidate in biology (with at best a basic understanding of calculus), I could follow along. That said, it's academically focused on theory, not practice. This is not the book you want if you aren't comfortable with mathematical (and probabilistic) equations and aren't interested in the theory behind probability. If you just want to be able to apply the stuff to practical problems, this book will get you there, but with way more theory than needed.

It's interesting, and a good book, if you want the mathematical and statistical foundations of probability theory. Explanations are good, examples are straightforward (except Example 1.23; there are two thinking errors in that one, leading to an incorrect answer), and R code isn't terribly hard to find to allow simulation to follow the examples in the book (Note: getting this book and following along will not teach you R). I would have benefited a bit more if the text were either dumbed down a bit (more english, less 'math'), or if my math background were more rigorous.

If you're mathematically-inclined, and want a good primer on probability theory, this would be a good choice. If you're looking to learn R, or want something more easily understood by those without a rigorous math background, this ain't your book.
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3 of 3 people found the following review helpful By I Teach Typing on February 2, 2014
Format: Hardcover Vine Customer Review of Free Product ( What's this? )
There are two good probability with R books on the market, this one and Probability with R: An Introduction with Computer Science Applications. Both are nicely written but they are designed for different audiences. Where Probability with R is readable by any educated audience, it has its examples firmly embedded in computer science. This one has appealing examples from all over the map. In probability with R the code is in the foreground. Here the R code is relegated to code insert boxes. Although the code is deemphasized it is present throughout and the website that accompanies the book has the script files. Beyond these two points, the largest difference between the two books is the emphasis on math. Probability with R is nowhere as mathematically rigorous. This book is designed for readers who have completed multivariate calculus and the math is prominent throughout. Each chapter has a set of probability problems. Sadly the author only includes solutions to half and the solution only has the answer not steps (code) needed to get the solution.

So, get this book if you are looking for engaging examples that are covered with code and a solid dose of math. If you are looking for more thorough coverage of R, get Probability with R instead.
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3 of 4 people found the following review helpful By Dr. Bojan Tunguz HALL OF FAMETOP 50 REVIEWER on February 3, 2014
Format: Hardcover Vine Customer Review of Free Product ( What's this? )
Probability is perhaps one of the most applicable and applied branches of mathematics today. This is in large part due to the fact that probabilistic reasoning underlies much of modern science and technology, which in turn are the backbones of the modern world.

There are many good probability textbooks out there, yet “Probability with Applications and R” stands out for several reasons. It is a textbook that effortlessly combines the theoretical and applied material, it is immensely up-to-date and relevant, and it uses computer simulations (and statistical language R in particular) in an organic and effective way. It is an almost ideal textbook for someone who wants to gain both the deep understanding and the hands-on experience with probability in an applied and relevant context.

This textbook was based on many years worth of experience teaching probability to upper level undergraduates at a liberal arts college. It assumes certain level of mathematical sophistication, and multivariable calculus in particular. Other than that, it’s open to a wide spectrum of students from a variety of majors and backgrounds – mathematics, physics, biology, computer science, etc. The chapters include “Conditional Probability,” “Random Variables,” “Continuous Distributions,” “Limits,” and several others. There is also a short background material on R that has been relegated to appendixes. R is a scripting language, and the student should be familiar with at least the rudiments of computer programming before engaging with the material in this book.

One of this book’s greatest features are the numerous examples, tutorials, exercises and “experiments.” All of them are very clear and pedagogical, and greatly foster learning and the acquisition of this material.
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1 of 1 people found the following review helpful By SYLJAX on June 11, 2014
Format: Hardcover Verified Purchase
I read all the reviews and it seems to me they are done by friends or acquaintance.

The author interjects humor in the text to make the subject matter more user friendly. I agree with previous reviews, the book is a gentle introduction to R by showing examples on modeling using the software.

The textbook is full of errors, even the published correction list has errors. The topics are some times not in logical sequence. For example, the concept of random variable was used before it was formally introduced, and concepts for distribution and counting were very muddled for beginners.

If you are looking to build a solid understanding for probability from the ground up, this is not a good book to start. And if you are looking to strengthen your skills on R, this book does not explain R commands.
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