- Series: Chapman & Hall/CRC Texts in Statistical Science (Book 112)
- Hardcover: 596 pages
- Publisher: Chapman and Hall/CRC; 1 edition (July 24, 2014)
- Language: English
- ISBN-10: 1466575573
- ISBN-13: 978-1466575578
- Product Dimensions: 10.1 x 7.1 x 1.3 inches
- Shipping Weight: 2.8 pounds (View shipping rates and policies)
- Average Customer Review: 4.3 out of 5 stars See all reviews (24 customer reviews)
- Amazon Best Sellers Rank: #100,250 in Books (See Top 100 in Books)
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Introduction to Probability (Chapman & Hall/CRC Texts in Statistical Science) 1st Edition
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"… a welcome addition … The authors–wisely, in this reviewer’s opinion–take special care to maintain a conversational tone to prioritize accessibility instead. The result is a very readable text with concepts introduced with a degree of clarity that should suit the beginner extremely well. … An additional feature is the extensive use, and related instruction, of the R programming language for computations, simulations, approximations, and so forth. … beginning students opting for easy-paced learning will find the book highly suited to the purpose … An e-book version of the book is available upon creating an account with the website vitalsource.com and redeeming a code provided with every print copy."
―International Statistical Review, 83, 2015
"A few months ago I reviewed Blitzstein and Hwang’s excellent modern Introduction to Probability, which is chock full of features to ease the student’s path. … Blitzstein and Hwang try everything possible to help the student understand the material. … Blitzstein and Hwang have problems with applications to just about anything you can think of … What it comes down to, in my opinion, is that Blitzstein and Hwang is an excellent book for a wide variety of audiences trying to learn probability."
―Peter Rabinovitch, MAA Reviews, October 2015
"Introduction to Probability is a very nice text for a calculus-based first course in probability. … The exercises are truly impressive. There are about 600 and some of them are very interesting and new to me. … The website has R code, the previously mentioned solutions, and many videos from the authors teaching the class. The videos are entertaining as well as informative. … In addition to the standard material for such a course, there are also very nicely done chapters on inequalities and limit theorems, Markov chains, and Markov chain Monte Carlo. … this is an excellent text and deserves serious consideration."
―MAA Reviews, August 2015
"Unique in its conceptual approach and its incorporation of simulations in R, this book is a welcome addition to the vast collection of probability textbooks currently available. … The topics covered in the book follow a fairly traditional order … The companion website for this textbook, stat110.net, offers supplemental materials to the textbook. There are more than 600 exercises in the textbook, and 250 of these exercises have detailed solutions available on the website. The website offers additional handouts and practice problems and exams, as well as over 30 video lectures available on YouTube or iTunes U. The book is also available as an electronic book. Overall, Introduction to Probability offers a fresh perspective on the traditional probability textbook. Its sections on simulation in R, emphasis on common student mistakes and misconceptions, story-like presentation, and illuminating visualizations provide a comprehensive, well-written textbook that I would consider using in my own probability course."
―The American Statistician, August 2015
"Full of real-life motivations and applications, this is a leisurely paced, exercise-laden text, which is also suitable for self-study. Each chapter ends with a Recap section, another section with R code snippets suggesting how to perform calculations and simulations with that program, and finally an Exercises section with an unusually large amount of exercises. Supplementary material is provided ... The book includes a redemption code providing access to an e-book version of the text ..."
―Zentralblatt MATH 1300
About the Author
Joseph K. Blitzstein, PhD, professor of the practice in statistics, Department of Statistics, Harvard University, Cambridge, Massachusetts, USA
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Top Customer Reviews
The practise problems have an excellent difficulty gradient, and I strongly advocate that those serious in studying the topic by themselves to simply do the problems in numerical order. The solution manual available on the internet give the solutions for the most pedagogically useful problems, and is also a must-have.
As an undergraduate, I had two quarters of probability as part of my statistics coursework. While I had a good professor, the text was terrible, and didn't motivate many important topics like conditional probability, conditional expectation, MGFs, PGFs, indicator random variables, inequalities, etc. I was able to apply the basic probability lessons I'd learned in these courses (in my job as a bioinformatician and statistical programmer), but I didn't see the bigger picture. Reading Frederick Mosteller's story of probability generating functions in the book (p. 263) perfectly encapsulates how I felt, "... he [a professor of the mathematics department] showed me [Mosteller] a generating function. It was the most marvelous thing I had ever seen in mathematics. It used mathematics up to that time, in my heart of hearts, I had thought was something that mathematicians did just to create homework problems for innocent students in high school and college." I have many other probability books bookshelf, but all are collecting dust because they teach probability in a way that reminds me of the homework problems Mosteller speaks of.
In contrast, every topic in this book is painstakingly motivated with "story proofs", real examples, historical anecdotes, and elegant mathematical connections to earlier concepts. These motivating sections not only make the material crystal clear, but also help you remember why certain theorems are important, and what the types of problems they allow you to solve (which is vital when you need to apply them for your own real world problems!). Furthermore, these examples make the book a fun read — I've had it for two days and I can't put it down. Also, I'm positively excited that the authors included later chapters on Markov chains, MCMC, and Poisson processes. This book covers a lot for its size, but clearly can't cover everything — my hope is that we'll see my books by Blitzstein and Hwang. Overall, I simply can't recommend this book enough.
1. The "story" approach. The rationale of the various probability distributions and key ideas are explained with nice crisp stories, which make them immediately understandable and easy to remember.
2. The emphasis and depth of treatment of conditioning; its significance and breadth of usefulness. This far surpasses any other treatment I've seen at this level.
3. The unusually detailed discussion of indicator random variables and their remarkable usefulness. This is also unique in my experience.
Overall, the level is perhaps just a bit deeper than most texts at this level, and does require engagement and effort. As a plus, Blitzstein's excellent Harvard stat110 lectures are available online.
For those particularly interested in random process, at this level I would also recommend as a supplement the well known text by Bertsekas and Tsitsiklis. It's a bit gentler overall, but I really like the chapter on Bernoulli and Poisson processes.
While going through the lecture series, I could not help but wish there were a textbook I could study from: something that spelled things out just a bit more; provided a few more examples; walked me through things a little bit slower. Enter Introduction to Probability. While I’m sure it could function perfectly well as a standalone text, this is truly the companion textbook to the course. It follows the same syllabus, has many of the same examples and includes all the homework and “strategic practice” problems for which there are full solutions online (and tons more). In addition, it provides more detailed explanations and of course, being a written document, allows you to pace yourself and review past material more easily than a lecture series could. I find myself frequently flipping back and forth, even if only to review the naïve and non-naïve definitions of probability. I have had so much fun learning from Dr. Blitzstein (and co-author Jessica Hwang) – more than I could ever have imagined on this subject. He brings the material to life and even though I am not in the field, I find myself thinking about uncertainty and probability all the time in my own work (anesthesiology).