**Unique Numbers**: 59205/65700 **Time**: MWF 10-11 **Room**:
RLM 6.118

**Class Web Page**:
http://www.ma.utexas.edu/users/mks/384Esp08/384Esp08home.html

**Instructor**: Smith, RLM 10.136, 471-6142, http://www.ma.utexas.edu/users/mks/index.html

**Office hours**: Office hours are posted on my home page. I
will need to cancel office hours now and then to accommodate meetings,
oral exams, etc. I will try to give you several days advance notice
when this happens. If it is impossible for you to make office hours, I
will
try to arrange individual appointments at other times.

**Text**: *Design and Analysis of Experiments*, Dean and
Voss, Springer, 1999

Please Note: The UT library has an e-book copy of the textbook.
If you use it, please use "view"
rather than "check out".
If you use "check out", then no one else will be able to use the e-book
for 24 hours. Also, be sure to "close" after viewing the book.

**Parts of Text to be Covered**: With some omissions, we will
cover Chapters 1 — 7, 10, 17, 18, and 19. As time permits, we may
also cover parts of Chapter 11. Occasional short additional topics may
be added.

**Focus of the Course**: This is an introductory course in Design
and Analysis of Variance. The course will be a mix of theory and
application. Some results will be derived, so that you get some feel
for why things are as they are. Most of what you will be expected to do
is apply the theory carefully and with understanding. This means I will
expect you to think about what you do. Do not expect rules that you can
use in a mechanical manner.

**Prerequisites**: An upper division undergraduate course in
statistics such as M378K, or a similar graduate course. Since
introductory statistics courses vary widely in their content and
emphasis, it is inevitable that most
students will be fuzzy on some of the prerequisite material. Therefore,
I
will give very brief reviews of most undergraduate concepts we use and
expect
you to consult appropriate references (e.g., the texts by Ross or
Wackerly
listed below) if needed.

**Assignments and grading**: Course grades will be based on five
problem sets, a take-home midterm exam, and a take-home final exam. The
problem sets will be due Fridays February 1, February
15, March 28, April
11, and April 25. The midterm will be due Friday, March 7 (the day
before spring break). The final exam will be due Saturday, May 10 at 10
pm (the end of the final
exam date and time listed in the course schedule for this
course). One homework
grade will be dropped, to allow for a
normal amount of illness, emergencies, bad weeks, and a learning curve.
The midterm and final exams will each count equally with each of the
remaining homework assignments
in determining the course grade, *but the exam grades will not be
dropped*.

*I will expect you to write up your homework solutions carefully.*
Do *not* hand in a rough draft. In particular:

1. Write in complete sentences.

2. Organize your presentation. In
particular, *put computer output and graphs as close as possible to
the place where you discuss or refer to them.* (Please do *not*
put them at the end of each problem.) This often requires cutting and
pasting (either by hand or computer). In some cases, writing on your
computer output will work.

3. Do *not* hand in computer output
that you have not referred to in your discussion. Again, this may
require cutting and pasting. But be
sure to include computer output that you have referred to in your
discussion.

4. *Explain your reasoning clearly*.
*The quality of your reasoning will be an important consideration in
your grade,* especially as the semester progresses and you have more
options available to consider. *Do not expect full credit if you do
not give reasons for your answers or if you do not interpret
your output in the context of the problem*.

5. Write legibly.

6. In any applied problem, state your conclusions carefully and in the context of the problem. For example, "We reject the null" is not an acceptable final conclusion. "Based on the p-value of .02, we conclude that the data do not support the null hypothesis that the mean weight of beans of type 1 is 3 and reject it in favor of the alternate hypothesis that this mean weight is > 3," would be much better (assuming the details fit the context).

I will also sometimes assign questions for discussion. **->**
Be sure to think about these before we discuss them in class. Their
purpose is to help you understand (and avoid misunderstanding!) some of
the subtleties involved in the concepts and their application.

I will also try to give you reading assignments so you can preview material if you choose.

Often I will post class lecture notes on the class home page the
night before lectures. I will email the class from Blackboard when
notes are posted. Be sure to check your email. (Note: If the University
has the wrong email address for you in Blackboard, then you will not
receive these or any other notifications of misprints, changes in due
dates, etc.)

**Policy on late work:** I am willing to accept *one*
slightly late *homework *assignment from each student. "Slightly
late" means after class on the day the assignment is due, but before
the grader picks up homework. Late *exams* may be subject to a
late penalty. I am always willing to accept assignments early. They may
be slipped under my door if I am not available. Extenuating
circumstances will be handled on a case-by-case basis. In particular,
according to Section 51.911 of the Texas Education Code,
a student who misses an examination, work assignment, or other project
due
to the observance of a religious holy day must be given an opportunity
to
complete the work missed within a reasonable time after the absence, *provided
that* he or she has properly notified each instructor. It is the
policy
of The University of Texas at Austin that the student must notify each
instructor at least fourteen days prior to the classes scheduled on
dates
he or she will be absent to observe a religious holy day. For religious
holidays that fall within the first two weeks of the semester, the
notice should be given on the first day of the semester. Alternate
arrangements will be made as soon as possible after notification.

**Computer software**: Minitab is the default software for this
course. I will use it and will give handouts on using it. I will accept
use of other software on assignments *provided*:

1. You don't ask me for help with the software. (In particular, it is your responsibility to put the data into a format appropriate for the software, if needed.)

2. It can do what is needed.

3. You don't use it to replace doing your part (in particular, thinking) on homework.

4. You interpret output assuming I am unfamiliar with the software.

In particular, students who have access to SAS may wish to use that
software; the textbook provides instructions in doing so. However, the
math department does not support SAS, although it currently has JMP,
which is related to SAS.

*Minitab availability*:

- Minitab is
available in math department compter labs. For information on obaining
an account and accessing data from the textbook, see
*Using Minitab in Math Department Computer Labs*. - Minitab is also
available on PC's in the Student
Microcomputer Facility. Follow
the link for location and information on how to obtain an account. See
the
handout
*Using Minitab in Math Department Computer Labs*for information on accessing data for the textbook. You may need to modify the instructions there slightly. - You may access Minitab by connecting remotely to the ITS Windows Terminal Server from your own computer. This requires an IF account validated for use of the server. You will need to pay extra charges for using this service. You will also need to configure your remote desktop. For more information , see http://www.utexas.edu/its/products/minitab/#Timesharing (Scroll down to the link just before System Requirements.)
- If you wish to purchase or rent your own copy of Minitab, see e-academy.

**Ethical matters**:

*Statistical ethics*: Statistics consists of a collection of
tools which, like any tools, can be used either for good or for ill. It
is your responsibility as a citizen of the world to be sure not to
misuse these tools. I encourage you to read the Ethical Guidelines for
Statistical Practice
developed by the American Statistical Association, available on the web
at http://www.amstat.org/profession/index.cfm?fuseaction=ethicalstatistics.

*Authorized collaboration*: Since the University defines
collaboration that is not specifically authorized as academic
dishonesty, I need to tell
you what collaboration is authorized in this class.

The following type of collaboration *is* *authorized* *on
homework*,
*but not on exams*: Working on homework with someone who
is
at roughly the same stage of progress as you, provided both parties
contribute
in roughly equal quantity and quality (in particular, thinking) to
whatever
problem or problem parts they collaborate on.

The following types of collaboration are * not authorized*:

1. Working together with one person the doer and one the follower.

2. Any type of copying; this includes splitting up a problem so that different people do different parts or obtaining solutions from students who took the course previously.

3. Any type of collaboration on exams.

Academic dishonesty aside, asking anyone, "How do I do this problem?" (as opposed to questions like, "How do I carry out this detail of this technique?" or, "I'm not sure whether to proceed this way or this way; here is my thinking about each possibility; am I missing something?"or "Can you read this over and critique it for me?") is cheating -- cheating yourself and your future employer, since it avoids the most important part of statistics: thinking.

**Students with Disabilities**: Please notify me as soon as
possible of any modification/adaptation you may require to accommodate
a disability-related need. You will be requested to provide
documentation to the Dean of Students' Office, in order that the most
appropriate accommodations can be determined. Specialized services are
available on campus through Services for Students with Disabilities.
For more information, contact the Office of the Den of Students at
471-6259, 471-4641 TTY.

**Additional references**: Here are some suggestions if you need
to consult another text. However, do *not* try to find solutions
to homework problems in another textbook. I expect you to think in
doing homework problems. If you look up the solution, you have largely
defeated the purpose of the problem.

*Other books on Analysis of Variance and Design of Experiments:*

Cobb, George W., *Introduction to Design and Analysis of
Experiments*, Key College/ Springer, 1998. This book is slightly
lower level than this course.
It does not go into derivations of the statistical procedures, but has
a
lot of detail on different experimental designs and gives many
intuitive descriptions.

Montgomery, Douglas C. *Design and Analysis of Experiments*,
Wiley, 2001. Another book that has been used as a text for this course.

*Books that may be useful for prerequisite material:*

Ross, Sheldon M., *Introduction to Probability and Statistics for
Engineers and Scientists*, New York, N.Y., Wiley, 1987, TA 340 R67
1987 Engineering Library. Another textbook on introductory statistics
that might be useful for review or reference.

Wackerly, Mendenhall, and Schaeffer, *Mathematical Statistics
with Applications*, Duxbury, 1996