Introduction to Probability, Statistics, and Random Processes

I have seen several texts related to probability and random processes over the years, and so far this is my favorite. The exposition is very clear, and the author strikes a nice balance between theoretical derivations and helpful examples. I was a little concerned about the "Introduction to..." portion of the title, but I was pleasantly surprised that the text goes well beyond the basics. I think that this will be most useful to people studying advanced topics like machine learning or multitarget tracking because the text bridges the gap between introductory probability ideas and the more advanced materials you will see in textbooks or research papers focused specifically on machine learning or Kalman filtering. Over the years, I have relied on other texts like "Probability, Statistics, and Random Processes..." by Alberto Leon-Garcia and the "Random Signals..." text by K. Sam Shanmugan and Arthur M. Breipohl when I need to review intermediate to advanced probability concepts. While those books have their strengths, I think that this is my favorite due to its clarity and nice organization.

I originally wrote a very lengthy review but to stave boredom on a long trip I re-read this book in its entirety and felt this review needed an edit. Disclaimer: I already had a graduate background in probability before I first encountered this book. This is the best introductory non-measure-theoretic probability book available in the English language. I have read a lot of introductory probability books such Ross, Feller (the introductory chapters in vol 1), Papoulis, Bertsekas, Blitzstein, Tijms, and more. This book stands out as the only one I can recommend in good conscience to someone with a background in nothing more than multivariate calculus and basic linear algebra. It doesn't matter who you are; whether you are embarking on a probability course at university for the first time, getting into machine learning, grad student looking for a refresher after several years, teaching probability to newcomers, trying to understand options theory, whatever. Want to learn probability? This book is the place to start. My two, and only two, points of criticism are that introduction to probability by Ross explains combinatorics much better, largely because it contains an incredibly long list of combinatorics exercises. Second, that many important concepts are hidden in the exercises. Not necessarily a bad thing because I'd hope newcomers actually do the exercises, but I'd rather they were explained in the main text. In summary, this is THE book to learn probability from. It will create an excellent foundation for you to embark upon any manner of probability topics. I would give it 6 stars if I could. For anyone wondering what to read after this, If you want to go in a very applied route i recommend stochastic processes by Dubrow accompanied by probability for statistics and machine learning by DasGupta as a supplementary reference.

Absolutely love this book! No other book on the market contains such mathematical rigor and yet still explains the concepts in a way that can be so clearly understood. A certain amount of mathematical maturity is expected, but outside requirements are kept to a minimum. To get the utmost from the book (or any book on probability), it is probably best to have had at least one semester of calculus and one of linear algebra. A basic understanding of proof writing and reading, would also help. With those caveats, you could self teach probability to a very high and rigorous level with this book.

This is a great introduction to probability, statistics and random variables. I surveyed many books because I will be teaching a course at Sonoma State University on the subject. Pishro-Nik has written a textbook that is easy to understand and has many examples. The fact that it is inexpensive is desirable for students and it is a tested book on the subject.

This textbook on probability is very simple and gradual. It starts with describing sets and slowly moves into probability. It assumes you know nothing about it from the beginning but appears to be thorough. The only problem is the binding which falls apart not much longer than when you crack open the book open. I got mine rebound through another vendor and it cost as much as the book itself but well worth it. I will probably reference this book for years.

I'm using this as a supplement to the main textbook that my university uses for their probability and stats course. Our main text takes a mouthful to explain a concept, whereas Pishro-Nik's explanations are clear, to the point, and just as detailed. For instance, when I was collecting all the discrete probability distributions in one notebook for reference, our main text did not have them clearly and concisely laid out. Pishro-Nik had them in one section, back-to-back, and each was formatted in a distinct box with their experimental conditions clearly spelled out. Remarkably easy to find.

I bought this book because the text used in my probability and statistics course didn’t explain the concepts very well. I found this book to be much better for me. There are a lot of practice problems and an available student solutions manual, which were very helpful for me.

Excellent book on Probability.

This is a brilliant book whose author has gone out of his way to demystify an hitherto convoluted and obscure subject. Prof Hossein Pishro-Nik is a great teacher both on camera and print. He effortlessly and successfully communicates the fundamentals with such expertise from a student standpoint. His pleasant pedagogy disabuses the dog-eared theorem-lemma of yore. A proper mastery of the first 7 chapters is adequate to provide a solid foundation to explore other advanced realms of probability as applied in different genres of statistics. Buying this book and investing time reading it, doing the exercises and watching the videos on the book's webpage amounts to more than a free intellectual gift to any consumer.

It's an amazing introduction to probability and statistical inference, if you are looking for a reference that's easy to read and well written this is definitely a great purchase

I bought the book in 2016. At that time there were no enthusiastic reviews. But already at that time I thought that the book was outstanding in detail and clearness presenting probabilistic concepts. I needed a book accompanying a course in probabilistic programming (WebCHURCH, WebPPL). My math-phobic students come from CS and Psychology. As the book is free online there is no excuse for them to avoid reading. As my course is Bayesian I recommend chapters 1-7 and 9. Then I move on with excerpts of Held & Bové's "Applied Statistical Inference: Likelihood and Bayes", Gelman's "Bayesian Data Analysis", or Koller's "Probabilistic Graphical Models".

This book is awesome. I just received this book and is only 3 pages in yet this book have begun shaping my thoughts and understanding for the topic. I am pursuing a BSc Psychology degree with zero knowledge in statistics and probability and this book is perfect for me. The examples given in the book are social science friendly. Majority of other statistics and probability books (including my school textbook) in the market are heavily written for engineering students and require some level of technical and even mechanical understanding, which is rather redundant for social sciences students like myself. There is a free version of this text online but I am a book person and buying this book is worth every cent. Thank you Mr Hossein Pishro-Nik for writing this book!

Excellent book. This is not one of those annoying "theorem, proof, theorem, proof, ... " books that seem to revel in terseness (is trying to be as concise and terse as possible some sort of math nerd thing?). The author gives a clear step by step exposition of the subject matter and goes the extra mile by explaining the intuition behind some of the more counter-intuitive aspects of the subject. If you are completely new to probability theory and want a book that, on the one hand, is not so superficial as to be useless, and, on the other hand, is rigorous and thorough without sacrificing clarity, then I heartily recommend this book.