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Introduction to Probability

4.51  ·  Rating details ·  78 ratings  ·  10 reviews
Developed from celebrated Harvard statistics lectures, Introduction to Probability provides essential language and tools for understanding statistics, randomness, and uncertainty. The book explores a wide variety of applications and examples, ranging from coincidences and paradoxes to Google PageRank and Markov chain Monte Carlo MCMC. Additional application areas explored ...more
Hardcover, 596 pages
Published September 3rd 2014 by Chapman and Hall/CRC (first published August 1st 2014)
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Deepak
Jan 18, 2016 rated it it was amazing
Sometime ago I got interested in machine learning. Since machine learning involves a good amount of statistics, I started looking for books or resources on probability. After abandoning two widely recommended books, I chanced upon Blitzstein's lectures, I felt that his book would have much more to offer than the lectures. I found it immensely interesting, the authors provide lucid explanations for every concept. There is a lot of emphasis on building intuition about statistical concepts. To driv ...more
Dan
May 19, 2019 rated it really liked it
This book starts from the basic concepts of probability theory and develops it up to the law of large numbers and the central limit theorem (and more). I really like the approach this book takes, with a more intuitive explanation of the concepts rather than just focusing on the mathematics, which often (for me at least) doesn’t provide any idea of *why* these probabilistic results should be true.

The book uses the concept of a “story” to define distributions, which is basically learning by generi
...more
Anthony Mowers
May 17, 2017 rated it it was amazing
I discovered that if I wanted to develop a solid foundation in machine learning then a familiarity with the basics of probability theory and statistical inference would be useful.

This book teaches basic probability and several of the more common statistical distributions in an academic but easy to read style. It's a good prep before learning statistical inference.

Prerequisite is only first year university level mathematics skills.
Oleg Dats
Oct 04, 2018 rated it it was amazing
Perfect supplementary material for the amazing course stats-101 by Blitzstein.
https://projects.iq.harvard.edu/stat1...
...more
Hanyu
Dec 12, 2017 rated it it was amazing
Absolutely amazing. Crisp and clean introduction. Questions are somewhat challenging.
Wendelle
Mar 11, 2018 rated it it was amazing
through this beautiful, explanatory book, i finally understood whatever it was that was going on in the formalism behind john a. rice's textbook.
Kent Sibilev
Mar 10, 2019 rated it it was amazing
Amazing course and one of the best introductions to the theory of probability.
Andi Geng
Oct 28, 2016 rated it it was amazing
This was a very good textbook. I should note that it focused on building intuition first, which was great for my purposes, but if you're looking for a super rigorous treatment this isn't it. It's a great introductory text. Paired with STAT 110 (the course for which this textbook was written for), you have a huge amount of practice material, in addition to lectures, fantastic notes, etc.

I'm not quite through (haven't done the sections on Markov chains), but this is a great textbook so far.
Goo
I read most of it for an introductory course on probability theory. Ever since then I reread parts of it whenever I need to refresh basic intuitions.

I couldn't imagine a better introduction to probability theory.
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May 05, 2018 rated it it was amazing
Without much exaggeration, this is the single most important book I have read in my life. It introduced me to the possibility of extending logic to the realm of unpredictability and chaos. The abundant amount of concrete and vivid examples helped me to appreciate many of the core concepts of probability and statistics. I sincerely recommend this book to anyone who wants a lucid, fascinating, and at times challenging read.
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