Probability and Statistics for Computer Scientists

by Michael Baron

In modern computer science, software engineering, and other fields, the need arises to make decisions under uncertainty. Presenting probability and statistical methods, simulation techniques, and modeling tools, Probability and Statistics for Computer Scientists helps students solve problems and make optimal decisions in uncertain conditions, select stochastic models, compute probabilities and forecasts, and evaluate performance of computer systems and networks. After introducing probability and distributions, this easy-to-follow textbook provides two course options. The first approach is a probability-oriented course that begins with stochastic processes, Markov chains, and queuing theory, followed by computer simulations and Monte Carlo methods. The second approach is a more standard, statistics-emphasized course that focuses on statistical inference, estimation, hypothesis testing, and regression. Assuming one or two semesters of college calculus, the book is illustrated throughout with numerous examples, exercises, figures, and tables that stress direct applications in computer science and software engineering. It also provides MATLAB ® codes and demonstrations written in simple commands that can be directly translated into other computer languages. By the end of this course, advanced undergraduate and beginning graduate students should be able to read a word problem or a corporate report, realize the uncertainty involved in the described situation, select a suitable probability model, estimate and test its parameters based on real data, compute probabilities of interesting events and other vital characteristics, and make appropriate conclusions and forecasts.

Genres: Computer Science, Mathematics, Textbooks

426 pages, Paperback

First published October 1, 2006

About the author

I grew up in the New York area and I’ve lived there my entire life. I worked in retail and taught high school English before I got my first book contract. I have gotten several additional book contracts since then, which is fortunate because I didn’t have the patience to work in retail and, while I quite enjoyed teaching, my approach was a bit too unconventional for most school systems. One school administrator told me that, “there are more important things than being a dynamic teacher.” Since I couldn’t name any of those things (at least in the context of school), I figured I didn’t have a long-term future in the profession. Hence, I became a writer, where I believe people appreciate a certain level of dynamism.


Though I started with nonfiction, I have always loved fiction and I have always wanted to write it. I’ve always had a particular affection for love stories. In fact, the very first book-length thing I ever wrote, when I was thirteen, was a love story. Mind you, it was the kind of love story that a thirteen-year-old boy would write, but it was a love story nonetheless. I have a deep passion for writing about relationships – family relationships, working relationships, friendships, and, of course, romantic relationships – and I can only truly explore this by writing fiction. These novels have given me a way to voice the millions of things running through my head.


My wife and kids are the center of my life. My wife is the inspiration for all of my love stories and my children enthrall me, challenge me, and keep me moving. One of the primary reasons I wrote my first novel, When You Went Away was that I wanted to write about being a father. Aside from my family, I have a few other burning passions. I’m a pop culture junkie with an especially strong interest in music, I love fine food (and any restaurant shaped like a hot dog), and I read far too many sports blogs for my own good.


You might have noticed that I haven't published a photo of myself. This isn't because I'm involved in the Witness Protection program or because I have an innate fear of cameras. It's because Michael Baron is a pseudonym. I'm writing these novels “undercover” because they're not entirely compatible with the nonfiction books I write and I didn't want to confuse readers. We're all different people sometimes, right? I just decided to give my alter ego another name.


My third novel, The Journey Home, has just come out. It’s a love story, too. Naturally.

Reviews

[Emil Petersen · Rating 4 out of 5]

I have read chapters 1-9 thoroughly; 10-12 not so much. The core material is solid and well explained. Lots of examples and convenient definitions here and there. Also a ton of useful exercises. A minor comment is that the examples are not really CS problems if you ask me, but rather general problems using CS words. Like jobs to a printer, number of emails received and things like that. This should not denigrate the book, because it really is very, very useful. Much of the statistical magic going on suddenly makes more sense. I have no regrets reading this (and it took quite a while).

[mirela Darau · Rating 4 out of 5]

- found it suitable for my Computer Science students. The main reasons for choosing it were the average mathematical level (theory is presented in a fairly simple mathematical context, which was great for my students), a good list of examples/exercises (ranging from very simple to rather complex, comprising computer science problems as well as famous probability ones, and others), and the convenient structure.

However, I found some of its sections pretty dry (like Descriptive Statistics or Continuous Distributions) and I wished for a couple of more complex problems in each chapter, as I find it good to challenge to the extreme also the abilities of good students :)

[I used it together with J.L. Johnson's book - to provide some more hard-core stuff - and with A. Vicker's statistics book - to get some spicy, practical examples]

[Darin · Rating 5 out of 5]

This has become my favorite introductory statistics books. What makes this different from many other statistics books is that the author states things that most authors assume (incorrectly) will be obvious to the beginner. Standard introductory material is included as well as chapters on simulation and stochastic processes that will be helpful to some computer scientists. Many of the examples are based on computer science, which is a plus for computer science majors, but shouldn't be a problem for non-computer science majors. There are some examples implemented in Matlab, although not much.

[Tim · Rating 5 out of 5]

As a CS major, I found this book perfectly geared for the intersection of Computer Science and Probabilities/Statistics. It covers the major application areas of the latter in the former in a relevant and efficient manner. It was used as the text book for a graduate level course that I took, and even though the professor turned the class into an undergraduate level statistics class, the book itself has been an excellent reference for my PhD work.

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