Introduction to Probability and Statistics Using R

by G. Jay Kerns

This is a textbook for an undergraduate course in probability and statistics. The approximate prerequisites are two or three semesters of calculus and some linear algebra. Students attending the class include mathematics, engineering, and computer science majors.

394 pages, Paperback

Published January 10, 2010

Reviews

[Adam · Rating 5 out of 5]

This is a great text in spite of being practically un-published, or rather freely distributed in a half-finished form. How you gonna do a Stats class without jumping into data? Well, this author doesn't. Rather than sink deep into apparently irrelevant Mathematics like so many similar textbooks do, he starts you off with data, with processing data in the free and extremely good programming language R, and jumps around between Math, programming, and Stats as he goes so that everything ties together in a very meaningful and integrated package. You don't have to have a background in essentially anything but a decent amount of Math to be able to learn all of the Stats and R that are contained in this, and relative to the subject matter it's a pretty easy read.

[Rajesh · Rating 5 out of 5]

Fantastic reference.

[Leo Walsh · Rating 5 out of 5]

This is a free, opensource text book written by G. Jay Kearns, a professor of Statistics at Youngstown State University. It is a good book to learn the R language from, but the material does require prior exposure to statistics since it is upper division text.



It is available from the site that hosts R.

More at Leo's Blog: leo-walsh.com.

[Veruska · Rating 3 out of 5]

The book tries to teach statistics/probability and the R language at same time but fails to do it well. But its a very good reference for those who have some statistics background.