\chapter*{Preface}
\label{preface}

Why is this book different from all other books on probability and
statistics?

First, the book stresses computer science applications.  Though other
books of this nature have been published, notably the outstanding text
by K.S. Trivedi, this book has much more coverage of statistics,
including a full chapter titled Statistical Relations Between Variables.
This should prove especially valuable, as maching learning and data
mining now play a significant role in computer science.

Second, there is a strong emphasis on modeling:  Considerable emphasis
is placed on questions such as: What do probabilistic models really
mean, in real-life terms?  How does one choose a model?  How do we
assess the practical usefulness of models?  This aspect is so important
that there is a separate chapter for this, titled Introduction to Model
Building.  Throughout the text, there is considerable discussion of the
intuition involving probabilistic concepts.  For instance, when
probability density functions are introduced, there is an extended
discussion regarding the intuitive meaning of densities in light of the
inherently-discrete nature of real data, due to the finite precision of
measurement.  

Due to the emphasis on intution, there is lesser treatment of
mathematical theory.  This book does not define probability spaces in
the ``mini-measure theory'' taken by most texts.  However, all models
and so on are described precisely in terms of random variables and
distributions.  And the material is somewhat more mathematical than most
at this level in the sense that it makes extensive usage of linear
algebra.

Finally, the R statistical/data manipulation language is used throughout. 
Again, several excellent texts on probability and statistics have been
written that feature R, but this book, by virtue of having a computer
science audience, uses R in a more sophisticated manner.  It is
recommended that my online tutorial on R programming, {\it R for
Programmers} (\url{http://heather.cs.ucdavis.edu/~matloff/R/RProg.pdf}), 
be used as a supplement.

As prerequisites, the student must know calculus, basic matrix algebra, and
have skill in programming.  As with any text in probability and
statistics, it is also necessary that the student has a good sense
of math intuition, and does not treat mathematics as simply memorization
of formulas.

A couple of points regarding computer usage:

\begin{itemize}

\item In the mathematical exercises, the instructor is urged to require that
the students not only do the mathematical derivations but also check
their results by writing R simulation code.  This gives the students
better intuition, and has the huge practical benefit that its gives
partial confirmation that the student's answer is correct.

\item In the chapters on statistics, it is crucial that students apply
the concepts in thought-provoking exercises on real data.  Nowadays
there are many good sources for real data sets available.  Here are a
few to get you started:

\begin{itemize}

\item UC Irvine Machine Learning Repository,
\url{http://archive.ics.uci.edu/ml/datasets.html}

\item UCLA Statistics Dept. data sets,
\url{http://www.stat.ucla.edu/data/}

\item Dr. B's Wide World of Web Data,
\url{http://research.ed.asu.edu/multimedia/DrB/Default.htm}

\item StatSci.org, at \url{http://www.statsci.org/datasets.html}

\item University of Edinburgh School of Informatics,
\url{http://www.inf.ed.ac.uk/teaching/courses/dme/html/datasets0405.html}

\end{itemize}

Note that R has the capability of reading files on the Web, e.g.

\begin{Verbatim}[fontsize=\relsize{-2}]
> z <- read.table("http://heather.cs.ucdavis.edu/~matloff/z")
\end{Verbatim}

\end{itemize}

This work is licensed under a Creative Commons Attribution-No Derivative
Works 3.0 United States License.  The details may be viewed at
\url{http://creativecommons.org/licenses/by-nd/3.0/us/}, but in essence
it states that you are free to use, copy and distribute the work, but
you must attribute the work to me and not ``alter, transform, or build
upon'' it.  If you are using the book, either in teaching a class or for
your own learning, I would appreciate your informing me.  I retain
copyright in all non-U.S. jurisdictions, but permission to use these
materials in teaching is still granted, provided the licensing
information here is displayed.