Introduction to Probability with R

by Kenneth P. Baclawski

Based on a popular course taught by the late Gian-Carlo Rota of MIT, with many new topics covered as well, Introduction to Probability with R presents R programs and animations to provide an intuitive yet rigorous understanding of how to model natural phenomena from a probabilistic point of view. Although the R programs are small in length, they are just as sophisticated and powerful as longer programs in other languages. This brevity makes it easy for students to become proficient in R. This calculus-based introduction organizes the material around key themes. One of the most important themes centers on viewing probability as a way to look at the world, helping students think and reason probabilistically. The text also shows how to combine and link stochastic processes to form more complex processes that are better models of natural phenomena. In addition, it presents a unified treatment of transforms, such as Laplace, Fourier, and z; the foundations of fundamental stochastic processes using entropy and information; and an introduction to Markov chains from various viewpoints. Each chapter includes a short biographical note about a contributor to probability theory, exercises, and selected answers. The book has an accompanying with more information.

Genres: Mathematics

380 pages, Hardcover

First published January 1, 2008

Reviews

[Terran M · Rating 5 out of 5]

This is my favorite introductory probability book; I especially like the interweaving of the math and the R commands. It goes considerably deeper into probability than your high school or college statistics class probably did, and I think it will give you an adequate foundation for reading most professional papers in data science.

This book covers probability, not statistics. My favorite introductory statistics book is Openintro Statistics by David Diez et al.

Be aware that this book contains numerous serious errors which have not been corrected in subsequent printings. You will want to download the errata and mark them up in the book prior to reading, or you will regret it when you spend an hour trying to understand something that turns out to just be a misprint.