**Unique Numbers**: 57285/64025 **Time**: MWF 10-11 **Room**:
RLM 6.118

**Class Web Page**: http://www.ma.utexas.edu/users/mks/384E09/M384Esp09home.html

**Instructor**: Smith, RLM 10.136, 471-6142, mks[at]math.utexas.edu,
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 6, February 20, April
3, April 17, and May 1. The midterm will be due Friday, March 13
(the day
before spring break). The final exam will be due Thursday, May 14 at 5
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. (Please 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*. (Please note: RLM open hours are M - Th 6 am - 11 pm, F 6 am - 10 pm, Sat 6 am - 5 pm, Sun 2 pm - 11 pm. Access after hours is by authorization and high security ID.) - 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/about/ethicalguidelines.cfm.

*Academic Integrity*: Any act designed to avoid partipating
honestly in the academic process is considered academic dishonesty by
this University. Examples of academic dishonesty include providing
misleading information to recieve an extension on an assignment,
plagiarism, and unauthorized collaboration. Instructors vary in
what kinds of collaboration are authorized. Here are the details that
apply to this course:

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.

The penalty for unauthorized
collaboration will be a grade of zero on the assignment or exam. Cases
of unauthorized collaboration or other acedemic dishonesty will be
reported to the Dean of Students office. See http://deanofstudents.utexas.edu/sjs/ for more information on academic information and its potential consequenceLecture

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