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\begin{document}

\title{ECS 256}

\author{Norm Matloff}

\date{Fall 2010}  

\input ../GenCourseInfo/MustKnowNOW256.tex

\section{Prerequisites}

The main required background is STA 131A (or equivalent, e.g. ECS 132 or
MAT 135A), a {\it calculus-based} course in probability.

That means that you have at some point in the past studied (and likely
forgotten, which is OK; see \ref{coverage} below):  random variables;
(one-dimensional) densities; famous parametric families of distributions
(at least binomial, geometric, Poisson, normal, exponential, uniform.)

This also implies that you will be able (again, after refreshing your
memory) to do:

\begin{itemize}

\item $\int_{0}^{\infty} \lambda e^{-\lambda t} ~ dt$

Derivatives, integrals, infinite series.

\item 
$
\left (         
\begin{array}{cc}
a & b \\
c & d
\end{array}
\right )^{-1}     
\left (         
\begin{array}{c}
e \\
f
\end{array}
\right )
$

Basic matrix operations, i.e. addition, multiplication and inverse.
(There is a review at the end of our textbook.)

\end{itemize}

It is also assumed that you have reasonable programming and debugging
skill; basic awareness of the concepts of bits/bytes, memory addresses
and data structures; experience in writing code to read and write files.

The \R language and \LaTeX word processing software that we will use in
this class are available for every major platform---Linux, Windows and
Macs.  However, {\bf I strongly prefer to that you run on Linux, as that
would make it easier to help you fix your bugs}.  So, a basic background
in Linux at the level of usage of ECS 40 would be helpful but not
required.  Prior background in \R and \LaTeX themselves is NOT required.

\section{Required Course Materials}
\label{text}

The textbook is my open source book.  You can buy it at the campus
bookstore (printed at cost), or can download it at 
\url{http://heather.cs.ucdavis.edu/~matloff/132/PLN/ProbStatBookF2010.pdf}.

You are required to have a hard copy of the entire text.

\section{Role of the Textbook}

Make sure you bring the textbook to every lecture. It will play a very active
role in the lectures.

Each day I will cover a portion of the textbook.  I typically will ask
you to open to a certain page, and then will call your attention to
various sentences, Examples and pictures on that page.  {\bf The
lectures will consist mainly of discussion and amplification of the
Examples in the textbook, with additional Examples and comments.}  I
will seldom write on the blackboard.

\textbf{SINCE THE TEXTBOOK ALREADY CONTAINS MY LECTURE, YOU DON'T TAKE
NOTES (other than miscellaneous comments in the margin).  THIS FREES
YOUR ATTENTION TO ASK QUESTIONS AND TO ENGAGE IN CLASS DISCUSSION.} You
are very much encouraged to bring up any questions you might have.
Please don't be shy about asking questions; there is no such thing as a
{}``dumb{}'' question. Similarly, listen carefully to the questions the
other students ask; this can be a very valuable source of insight, to
which you should pay special attention.

After each lecture, you should read in detail whatever portion of the
notes was covered.  Again, note that you should read all the details, as
there is not enough time during lecture to discuss all of them.

\section{Course Content}

\subsection{Topic Coverage}
\label{coverage}

I tend to end up covering less material than I had hoped at the
beginning of the quarter.  So, the following is a goal, probably not
fully achieved.

\subsubsection{Review of Undergraduate Prerequisite Material}

It will be presumed (with high probably, correctly) that you have
forgotten what you learned in your probability prerequisite course.
Thus in the beginning, there will be a semi-guided self-review, of the
following chapters in the text:

\begin{quote}
Ch.1:  all                                                             

Ch.2:  all                                                          

Ch.3:  all except Sec. 3.12

Ch.4:  through Sec. 4.5
\end{quote}

The self-review is ``semi-guided'' in the following sense.  I will
actually begin lecturing with Chapter 5.  Most of that chapter is likely
material not in your prerequisite course (or covered there just
superficially).  While lecturing on Chapter 5, which is on multivariate
distributions, I will constantly make comparisons to the univariate
case, using that as review.  Meanwhile, you will be reading the above
chapters, doing homework in them that I assign, and taking one or more
Quizzes on that material.

\subsubsection{Core Course Topics}

The core of the course will consist of:

\begin{quote}

advanced probability:

\begin{itemize}

\item Ch.5, multivariate probability models:  through Sec. 5.11

\item Ch.10, Markov chains:  all

\item Ch.11, renewal models:  all

\item Ch.12, queuing models:  all

\end{itemize}

statistics/machine learning:

\begin{itemize}

\item Ch.6, simple confidence intervals and significance tests:  all,
but quickly, as most students have seen this, maybe even in high school

\item Ch.7, advanced statistics:  Secs. 7.1, 7.2, 7.3, 7.8 

\item Ch.8, model development and selection: all

\item Ch.9, regression models and machine learning: all

\end{itemize}

\end{quote}

\subsection{What You Will Get Out of the Course}

\begin{itemize}

\item Acquisition of valuable research tools:  Many fields of CS and EE
make heavy use of probability and statistics.  After this course, you
will have a good foundation from which to apply these tools, learn more
about them and even develop your own new tools.  You'll be able to read
and understand statistical applications in the research literature, and
even spot what's wrong with them (plenty, in many cases!).

\item Impact on your daily life:  Applications of probability and
statistics show up everywhere---in election polls, in medical diagnosis,
in insurance, in casinos, in the courtroom, and so on.  What does all
this mean, in a real, practical sense?  Again, I'm not talking about
formulas---the issue is, what does it really MEAN?  You will get a
pretty practical understanding of these concepts in our course.

\item Acquisition of software tools:  In this course, you will learn the
basics of the R statistical programming language, which is the ``gold
standard'' for data analysis, and \LaTeX, a word processing package that is
standard in conferences and journals.  For links to my tutorials on R
and \LaTeX, see our course Web page,
\url{http://heather.cs.ucdavis.edu/~matloff/256.html }.

\end{itemize}

\section{Homework}

\subsection{Amount of Work}

There will be about four or five written homework assignments during the
quarter.  These will consist mainly of mathematical analysis but
sometimes will involve some light programming.

\subsection{Writeups}

Analytical work must be written in \LaTeX.  See below.

All programs and graphs must be done in R.

\subsection{Homework Partners}

You are required do your homework together in groups, with group sizes
to be announced (probably 3-4).  Your group submits the homework
together; make sure to include your group members' names in your
writeup.

{\bf You must submit to me your group membership lists by 11:59 p.m.  of
the day of the third lecture.  If you are not yet in a group, or have
only a partial group, ask me to assign you to a group.  Later, notify me
immediately if, due to drops, your group size falls below the minimum
group size.}

In working with your partners, you must work TOGETHER, instead of simply
dividing up the work among the partners.  

\subsection{Submitting Homework}

In order to facilitate grading, whose processing I will perform partly
by shell script, I will require homework submission to be done {\bf EXACTLY}
according to the following rules:

\begin{itemize}

\item Homework is due by 11:59 p.m. on the due date.  Submit just one
copy of your group's work, with all names on it.  Submission is by
e-mail to me.

\item Title your e-mail message ``HwknX,'' where n is the homework
number in Roman numerals and X is a string consisting of the first four
letters of each surname in your group (in alphabetical order).  For
instance, if the surnames of your group members are Crocker, Hopkins,
Huntington and Stanford, then the title of your e-mail message for
submitting Homework II would be HwkIICrocHopkHuntStan.  If I have the
homework due in stages, then the message titles would be
HwkIIACrocHopkHuntStan,  HwkIIBCrocHopkHuntStan and so on.

\item Your message should consist of one attachment, a Unix {\bf .tar}
file, with the name ``HwknX.tar,'' with X as above, in which the
following are packaged:

  \begin{itemize}

   \item Your writeup, in both {\bf .tex} and {\bf .pdf} files.  {\bf
   The PDF files MUST be viewable by xpdf on the CSIF machines.}

   \item Any graphs, in {\bf .pdf} files.

   \item Any code, in {\bf .r} files.  Make sure to put your NAME in the
   comments!

   \item A shell script ({\bf bash} or {\bf tcsh}) which runs your R
   code, if any.

   \end{itemize}

Do NOT make a subdirectory.  My automated shell script will apply {\bf
tar xf} to your {\bf .tar} file and will then expect to see your files
as listed above.

\end{itemize}

I apologize in advance for all this regimentation, but it will enable me
to grade your homework more quickly and with better feedback.  Thanks in
advance for your cooperation.

\section{Quizzes and Exam}

In the past, I have just given an Exam on the last day
of lecture.  However, I found that this just caused students to fall
behind.  So in addition, I will also have three short Quizzes.

Each Quiz will be about 15 minutes long, and will consist of two or
three short problems.  I will still lecture on days on which I give
Quizzes.

The Quizzes will be taken on an open-materials basis.  Make sure to
bring your textbook and any other written course materials, and you are
welcome to bring in anything else you consider helpful, e.g. probability
textbooks, English dictionaries, lucky charms, etc.

I will again give an Exam on the last day of class, occupying the entire
class period.  You will together with your homework group on the Exam.

{\bf Please make sure to bring your textbook to all Quizzes and the Exam.}
You will need it---many questions will refer to specific page numbers in
the textbook.

\section{Grading}

The grading components will be as follows:

\begin{itemize}

\item Homework, 40\%.

\item Quizzes, 40\%.

\item Exam, 20\%.

\end{itemize}

In recognition of the fact that you may be forced to miss a quiz due to
illness and the like, I will drop your lowest quiz grade.

The threshhold for a grade of n is (n-1).85; the threshhold for an `n-' grade
is (n-1).6; the threshhold for a `+' grade is n.2. So, for example, if your
weighted average from the above formula is between 2.6 and 2.84, your course
grade is B-; if the average is between 2.85 and 3.19, your course grade is B;
if the average is between 3.2 and 3.59, your grade is B+.

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\end{document}