M 358K: Applied Statistics Unique Number 57250 Spring
06
Instructor:
Professor M. Smith RLM
10.136 mks@math.utexas.edu 471-6142
Office hours: Posted on my home page, http://www.ma.utexas.edu/users/mks/
Class web site: http://www.ma.utexas.edu/users/mks/358Ksp06/358Ksp06home.html
(This page is linked from Blackboard.)
Prerequisite:
M362K (or equivalent) with grade of C or better.
Text: Introduction
to the Practice of Statistics, 5th edition, 2005/6, by Moore and McCabe. We will
cover Chapters 1- 10, with
occasional sections omitted. (The sections on probability are largely review,
and so will be covered more
quickly than the sections containing new material.)
The text will be supplemented with
occasional lectures and/or notes going into the more mathematical aspects of
the subject.
Nature of the course:
Statistics
is a mathematical science rather than a branch of mathematics. Thus this course
will have many aspects of a typical math course, but many aspects that are not
typical of math courses. Some things to
expect:
- In
many problems you will need to combine common sense and everyday knowledge with
mathematical and/or statistical techniques.
- Some
questions on homework and exams will not have one correct answer; your grade on
such questions will depend largely on the case you make for your answer, rather
than just on the answer itself.
- Reading
assignments from the text will be given. These need to be read with attention
to detail as well as to getting the general idea.
- Learning
new technical vocabulary is important. Some of it will be new technical
meanings that are different from everyday meanings of words.
- Writing
carefully and precisely is important.
- Class
participation is expected.
- You
will be expected to do a group project.
Grading: Grades will
be based on the following:
Written
homework
20%
Project 20%
Two
midsemester exams 15%
each
Final
exam 20%
Class
participation
5%
Pop quizzes
5%
This may seem like an unusual grading scheme for a math
class, but part of the reason is that statistics is only partly math. I believe
that it is not possible to evaluate accurately what you have learned and done
in this class solely on the basis of problems that can be done within the time
limits of an exam. Therefore homework problems and a project, which you can
spend more time on, will be important parts of your grade.
As
mentioned above and below, grading will be based not just on the final answer
or on calculations, but also on the reasoning shown in arriving at your final
answer.
Homework: You will
be assigned three types of homework:
1.
Reading assignments. The textbook is unusually well written, so we can make
best use of it and class time by your doing reading assignments before coming
to class. Then we can spend class time going over the more difficult parts of
the reading, reinforcing and applying what you have read, and supplementing the
text with some of the mathematical reasons behind the techniques. Be sure to
read for understanding and not just superficially. Thinking about what you read, and about what we do in class,
is important for learning statistics.
Pay special attention to the points marked with the "caution" symbol in the margin of the book.
2.
Practice exercises. These will usually have answers summarized in the back of the book. You will not hand these in,
but you will need to do them to help learn the skills and concepts that you
will need to put together to do the problems on written homework assignments.
Be sure to do them before the date they are assigned for, so you can ask
relevant questions based on preparation and understand class discussion. (We
won't be able to discuss all practice exercises in class.) Usually practice
exercises will be assigned together with the reading that they cover, to help you understand and assimilate
the reading.
3.
Written homework. These problems will usually be longer and/or more
involved than practice
exercises and exam questions.
Consider each written homework assignment as a mini-take-home exam. See
Guidelines for Written Homework and Policy on Late and Make-up Work below. Also
bear in mind that the answers in the back of the book are just summaries;
your solutions to written homework need to be more detailed and show your
reasoning more than the answers in the back of the book.
Guidelines for written homework:
1.
Remember that one important purpose of written homework is to practice thinking
statistically and to show me how well you have progressed in your thinking. Be sure to show
your reasoning -- I can't evaluate it if
you don't show it. And keep in mind the following quote from the instructor's
manual for our textbook:
If
we could offer just one piece of advice to teachers using IPS, it would be this: A number or a graph,
or a formula such as "Reject H0,"
is not an adequate
answer to a statistical problem. Insist that students state a brief conclusion in the context of the specific
problem setting. We are dealing with
data, not just with numbers.
In particular, just handing in computer output is not
satisfactory. You will often need to
include part of the output with your solution, but you need to explain how it
helps you solve the problem.
2. Do
not hand in a rough draft! Be sure to spend time organizing and writing your
solution. Ask yourself if you would like to read your write-up. If not, rewrite
it! Part of your grade will be based on clarity of organization and
explanation. After all, communicating well
is part of thinking well -- and making the effort to communicate clearly is an
important way to develop your thinking.
Do
not hand in extra computer output. Cut and paste (either by hand or on a word processor) so that figures and computer output come as close
as possible to the point in your discussion where you refer to them. In some cases, writing on computer output (especially printouts of graphs) will work.
Reminder: Answers in the back of the book are summaries,
condensed to fit in as little space as possible. Do not use them as models for written homework.
3. Write in complete sentences.
4.
Pay attention to correct use of vocabulary. You
will be learning technical
vocabulary in this course. Part of what you need to learn is to use it
appropriately. Be especially careful of what in language learning are
called "false friends:" words that are familiar, but have a technical
meaning that is
different from their common meaning. "Significant" is one example of
such a
word.
Also
be careful not to use mathematical vocabulary inappropriately in a statistical
context. In mathematics, we can often prove an assertion. In statistics, we
can usually only conclude that our result supports, suggests, or gives evidence
in favor of a conclusion.
5.
Use symbols correctly. One symbol often misused is the equal
sign. Do not use it except to mean that the two things it is between are
equal!!
If
you introduce a symbol, be sure to define
what it means. Common ways to do this include:
Let
µ be the mean of X.
Denote
the mean of X by µ.
Let
µ stand for the mean of X.
Be
careful not to let the same symbol stand for two different things in the same
problem. Subscripts can often be used to
avoid this confusion.
Project: You will be
expected to do a class project that will involve conducting a statistical study
from beginning to end: formulating the question, designing the study, carrying
out the study, analyzing the data, and reporting your conclusions. The purpose
of the project is to give you a deeper understanding than can be obtained by
shorter assignments of the different aspects of statistics (especially the
non-mathematical aspects) and how they fit together in practice and are
implemented.
Except
in unusual extenuating circumstances (e.g., someone who lives in Waco and is
only in Austin for three hours each
MWF), you will work on your project in a group of three or four people,
since that will let you learn from discussion with other group members, and
will reduce the work for any one individual in collecting the data.
You will have two preliminary
project assignments throughout the semester, which will count as part of your
project grade. The bulk of your project grade will be based on your final
report, which will be due the last day of class.
I
will give you more details as the semester progresses and we have introduced some necessary concepts and terminology.
Exams:
Do
not expect exams to be just like homework. Exam
questions will on average be less involved computationally than homework
problems. They will often focus in more depth than homework on conceptual
understanding. For example, some exam questions will test to see if you can
distinguish between similar concepts. Others will be "summing up" questions to
test how well you have been thinking as you learn. Others will provide you with
computer output and ask you to answer questions based on that output and a
description of the study from which it came.
Midsemester exams are tentatively scheduled for Friday, February 24 and Friday, April 14 during regular class time. Dates will be firmed up by no later than two weeks before the exam. If you have any serious
problem with either of these dates or possible alternate dates, be sure to let
me know no later than Wednesday, January 25.
The
final exam will be Monday, May 15, 2 - 5 p.m. I will not give early finals, so be sure you will be in Austin
that day.
Class Attendance and Participation: This is important for two reasons:
1. We will be covering material in class that
is not in the textbook.
2.
Discussion is very helpful in learning statistical concepts and statistical
thinking.
Since
the class is fairly large for class discussion, I will divide the class
into
two groups, which will alternate taking primary responsibility for
responding to questions
in class. When it is your group's turn to be responsible, be prepared
to put solutions on the board or the doc cam as well as answer
questions on the reading and exercises. But remember that answers to
questions that have answers in the back of the book usually need to be
more detailed than the answers in the back of the book, need
explanations, and need to be rephrased in your own words.
Of course, you will need to do assignments for all days, since one
day's assignment typically builds on the previous day's.
Please note:
I expect students to make mistakes in class participation. Sometimes we
learn best from our own or others' mistakes. What I look for in class
participation is that you are trying, and thinking.
Policy on Late and Make-up Work:
1.
Late homework will not be accepted
except under very extraordinary circumstances. (e.g., emergency
hospitalization) To allow for the normal number of illnesses, car
breakdowns, bad weeks, etc., I will drop the lowest three homework grades in
calculating your homework average.
2.
There will be no make-ups on midsemester exams. If you have an excused absence on a midsemester exam, I will
count your final exam grade in place of the missing exam grade. I
will not give you an excused absence unless (a) you request one as soon as
feasible (before the exam if that is possible) and (b) the absence was for good
cause (oversleeping or having other exams or papers due that day or week are
not considered good cause.)
3.
Late project assignments will be accepted , but your grade will be lowered by
one letter grade per day late.
Ethical matters:
Statistical ethics: Statistics
consists of a collection of
tools which, like any tools, can be used either for good or 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 and unauthorized collaboration: Since the University defines collaboration that is
not specifically authorized as academic dishonesty, I need to tell you what
collaboration is and is not authorized in this class.
The following types of collaboration are authorized:
1.
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. In fact, I encourage this type of collaboration!
2.
A moderate amount of asking, "How do I do this on Minitab?" However,
as you gain enough familiarity, you should get in the habit of using on-line
help and trying logical possibilities, then asking for help only if these don't
succeed after a reasonable try.
The following types of collaboration are not authorized:
1.
Working together with one person the do-er and one the follower.
2.
Any type of copying. In particular, splitting up a problem so that different
people do different parts is not authorized collaboration on homework. (A
certain amount of this may be appropriate on your project.)
3.
Possession or consultation of the Instructor's Solution Manual.
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?") is just cheating, since it avoids the most important part of learning statistics:
developing your statistical thinking skills.
Use of Technology:
General Computer Use:
You need to have access to email and the web.
- Homework assignments will usually be posted on the
web.
- I will sometimes post class notes on the web before lectures.
- You might be given assignments that involve use of
the web.
- I will sometimes send email messages to the class
using Blackboard. If the University does not have your current email
address, you will miss these.
Calculators: You will
need at least a garden variety calculator (that can do square roots) to do
occasional messy calculations.
On
exams, I will not allow use of programmable calculators -- this means graphing
calculators, in particular. However, you should bring a calculator capable of
taking square roots.
Computer Software: You
will need to use computer software. The default software for this class is Minitab. I have posted basic instructions on using
Minitab, but the instructions will get less detailed as the semester progresses. The instructions are for the Windows version that is on the
math department computers. Other versions will vary slightly, but it is fairly
easy to make the necessary alterations. Be sure to use on-line help and make
educated guesses.
I will accept use
of other software packages provided:
1.
You don't ask me for help with them.
2.
They can do what is needed.
3.
You don't use them to replace doing your part (in particular, thinking) on homework.
4.
You interpret output assuming I am unfamiliar with the package.
Minitab availability:
Minitab is available in the following ways:
- Minitab for Windows is available at the Student Microcomputer Facility (SMF) in
FAC 212. See http://www.utexas.edu/smf/
for information on how to open an account to print in this facility.
- A
Windows version of Minitab is available
via a Windows emulator. You can get a math department computer account
in the
Undergraduate Math Computer Lab ("The Big Lab"), RLM 7.122. Star
Office, similar to Microsoft Office, is also available in the
lab. For more information on using the lab, see the
handout Using Minitab in M 358K.
- 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/cc/sds/products/minitab.html#Timesharing
(Scroll down to the part that says "Using MINITAB on ITS Timesharing Systems".)
- If you wish to purchase or lease your own copy of Minitab, here are a couple of possible sources:
- e-academy offers 5-month Minitab for Window rental for $29.99
- Academic Superstore offers a Student Edition of Minitab for Windows for $55.95.
Data: Many homework
assignments will use data from the disk that comes with the textbook. You
cannot use this disk directly on the department computers, but I have put the
data in the department files so that you can access it. You can also download the data sets in various formats from http://bcs.whfreeman.com/ips5e/.
Students with disabilities: Please notify me 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.
Drop dates: The last date to drop a course for a possible refund
is February 1. The last day to drop a course without possible
academic penalty is February 13. The last day to drop a except for
urgent and substantiated nonacademic reasons is March 27. After
this, students may go to their Dean's office to appeal for non-academic
reasons.
LETTER TO M 358K STUDENTS
Dear M 358K student,
Welcome to M358K. I hope this class will be
rewarding for you.
Statistics is not the same as mathematics, although
it uses mathematics and you can bring many of your mathematical skills
to the subject. In your probability course, you dealt with matters that
were not as certain as most students expect mathematical topics to be.
Statistics deals with uncertainty even more than probability does. The
reason is that many aspects of real life are uncertain, and statistics
studies precisely those uncertain aspects of real life. So be prepared
to deal with some problems that are inherently messy, where you can't
get the exact answer. However, not being able to get an exact answer
does not mean
that any answer is as good as any other. You need to use valid
procedures to obtain your answer, and/or justify it by the specifics of
the context. Good writing skills therefore become important. Using
vocabulary appropriately and correctly is also important. So be sure to
learn the technical meanings of terms, and to avoid confusing them with
everyday or mathematical meanings. Also remember that in statistics,
because we are constantly dealing with uncertainty, we don't "prove"
things about the real world; we can just say whether or not the
evidence supports a possible conclusion, and sometimes we can even say
how well the evidence supports a possible conclusion.
I believe that learning best takes place when the
learner has an appropriate balance of challenge and support. This
course provides ample opportunities for challenge for most students
(although just what is challenging may vary from student to student). I
have tried to
build some support mechanisms into the course structure. These include
trying to make clear my expectations for you, giving study guides for
some reading assignments, using class activities, simulations, and
demonstrations to help aid understanding, incorporating mechanisms to
promote class
participation and reinforcement of material, and having you write and
have accepted a project
proposal before starting on your class project. However, the
individual student must accept responsibility for making the most of
these support mechanisms, for giving adequate time to the course, and
for finding other support mechanisms that might be needed. Different
students have different needs, but here are some possibilities that are
helpful for most students:
- Establishing a good relationship with one or more students
in the class with whom you can discuss class work (Two heads are better
than one!) or from whom you can obtain constructive emotional support.
(Of course, you should be willing to expect to give as well as take in
any such relationship.)
- Managing your time carefully so that you don't get behind. You will have assignments for almost every class, so be sure to
plan accordingly.
- Paying attention to the guidelines I have given in the
above First Day Handout, and that I will give in daily assignments and
the Project assignments
- Practicing constructive self-talk. (Example: If you start
thinking that you are "dumb" because you didn't see on your own
something that seems obvious after someone else explained it, remind
yourself that that happens to everyone, including extremely smart
people.)
- Making maximum use of your own and others' mistakes as
learning experiences.
Many students find statistical concepts and statistical thinking
difficult at first . Don't let the inevitable frustrations stop you.
Keep coming back to the concepts, and keep on thinking. It really helps.
I look forward to seeing you learn and appreciate statistics and its many applications.
Sincerely,
Martha K. Smith
Professor of Mathematics