OVERVIEW:
The materials here form a textbook for a course in mathematical probability and statistics for computer science students. (It would work fine for general students too.)
"Why is this text different from all other texts?"
For instance, the chapter on continuous random variables begins by explaining that such distributions do not actually exist in the real world, due to the discreteness of our measuring instruments. The continuous model is therefore just that--a model, and indeed a very useful model.
There is actually an entire chapter on modeling, discussing the tradeoff between accuracy and simplicity of models.
For topical coverage, see the book's detailed table of contents.
The materials are continuously evolving, with new examples and topics being added.
Prerequisites: The student must know calculus, basic matrix algebra, and have some minimal skill in programming.
LICENSING:
This
work is licensed under a Creative
Commons Attribution-No Derivative Works 3.0 United States License.
Copyright is retained by N. Matloff in all non-U.S. jurisdictions,
but permission to use these materials in teaching is still granted,
provided the authorship and licensing information here is displayed.
I would appreciate being notified if you use this book for teaching,
just so that I know the materials are being put to use, but this is
not required.
The book is freely available, subject to the conditions above, and can be downloaded from http://heather.cs.ucdavis.edu/~matloff/132/PLN/probstatbook/ProbStatBook.pdf.
AUTHOR'S BIO:
Norm Matloff is a Professor of Computer Science at the University of California, Davis. He was formerly a statistics professor at that university, and thus approaches the subject matter here as both a statistician and computer scientist. His research has included a number of diverse areas in the two fields, and he has been a recipient of the university's Distinguished Teaching Award. He was born and raised in Los Angeles, and earned his PhD in theoretical mathematics (probability theory/functional analysis) at UCLA.