The class will introduce you to the Windows
version of SPSS.
The current version is 13.0.
VCU has a site license that
allows us to distribute SPSS for Windows to all students, faculty and
staff. For a nominal fee of $15 you can get a CD-ROM that contains
version 12.0 at the VCU ONLINE
stores in the Student Commons and the MCV Campus Bookstore. This is a
really good deal! I urge you to buy and install this software on your
own computer if it satisfies the minimum requirements. SPSS says that
minimum requirements are Microsoft® Windows® 95, 98 or NT®
4.0, 68MB available hard drive space, and 32MB RAM. I would not recommend
using it without at least 64MB RAM, however.
I will assign some computer work outside
of class. If you do not have a PC that you can install SPSS on, you can
use a VCU computer to do these assignments. The computers in the public
access lab in Hibbs are setup identically to the ones in B008, and most
of the other public access computer labs at VCU have SPSS installed.
Your school or department may also have a computer lab with SPSS available
to graduate students. Prentice-Hall
publishes a lot of SPSS books. The most widely known is probably the Guide
to Data Analysis by M. Norusis. The first edition appeared
some 20 years ago, and it has evolved along with the software. This book
is a handy reference text to SPSS usage and statistical methods. It costs
over $60, however, and a used copy of earlier versions of the book will
serve almost as well. A less expensive Brief
Guide to SPSS is also available, but I would rather have
you learn to use the excellent online help in SPSS. http://www.at.vcu.edu/faq/spssonlinedoc.html
.
You do not really need books like these for this course!
The final exam will have a take-home
and an in-class segment. There will also be two quizzes during the
semester. These tests will make up 40% of the grade. Graded homework assignments
will make up 40% of the grade, and the remaining 20% will be based on class
participation including journals (see below) and, of course, attendance.
There will be 3 or 4 graded assignments during the semester. Usually
you will have a week to work on them.
I will mention my favorite problems from
each chapter of A&F as we go along. Short, primarily numerical,
answers to many odd-numbered problems are included in the text. You should
work on these exercises and browse others to see what the authors consider
to be "interesting questions." It is a good idea to keep a looseleaf workbook
of exercises and you should turn some of them in to get maximum
benefit from your tuition. Even if they are not part of graded assignments
I will be glad to critique them. I will comment on some in class even
without being asked to.
I urge you to review, revise and resubmit
exercises and graded assignments that you have trouble with. Studying in
groups is an excellent idea, but unless otherwise noted collaboration
is not permitted on graded assignments.
I want you to keep a journal,
containing your reactions to the text and to outside readings, as well
as to the lectures and exercises. A journal is a way to reflect on
problems, lectures and reading, distinct from class notes and problems.
Keep an eye out for writing in your discipline that reports statistical
research or applies statistical methods, and include in your journal items
that relate to the course in some way. You will find the class more useful
if you keep alert to how its topics show up in your everyday reading, both
professional and non-professional. It turns out to be very useful to write
about statistical ideas and problems, not simply to ask a question
and hear a reply. Statistics is not
simply a matter of calculating and reporting numbers, it demands interpretive
and rhetorical skills as well.
Most students find it convenient to submit
journal entries, problems and assignments by e-mail. I find it convenient
to receive them that way!
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August 30
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Chapters 1, 2
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Data, Sampling, Quick
Tour of SPSS
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September 8 (Wed.)
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Continued
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Data entry and editing
in SPSS
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September 13
|
Chapter 3
|
Univariate summary
statistics and related graphics
|
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September 20
|
Chapter 4.1, 4.2
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Probability Distributions;
Assignment 1 due
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September 27
|
Chapter 4.3 - 4.6
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Sampling Distributions
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October 4
|
Chapter 5.1
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Estimation; Quiz
on Ch 1-4
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October 11
|
Chapter 5.2-5.4,
5.6
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Confidence Intervals;
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October 18
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Continued
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Complex Sampling
Issues; Assignment 2 due;
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October 25
|
Chapter 6.1 - 6.3
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Significance Testing,
means and proportions;
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November 1
|
Chapter 6.4, 6.5,
6.8
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Significance Testing
Issues; Withdraw date Friday
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November 8
|
Chapter 7.2, 7.4
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Comparing two proportions;
McNemar test; Quiz on Ch 5-6
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November 15
|
Chapter 8.1, 8.2
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Chisquare tests;
Assignment 3 due
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November 22
|
Chapter 8.3 - 8.7
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No Class Wed.
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November 29
|
Continued
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Association in Contingency
Tables
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December 6
|
Review
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December 13
|
Final Exam
Scheduled Wed.
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Final Assignment
due Monday
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A
remarkable presentation of the roots of modern statistics.
Although
MacKenzie writes as a sociologist of science, his evaluation of the work
of Francis Galton, Karl Pearson and R.A. Fisher provides an excellent summary
of their contributions to the development of mathematical statistics as
we know it today. His sociological thesis is that the
primary concepts of statistics were "invented", not "discovered",
and that the social position of these men strongly influenced the
content of their works. While this not a radical position today (at least
in sociological circles) it was, in 1987, relatively unfamiliar to many
statisticians.
All
three of the major figures studied were connected to the eugenics movement,
and MacKenzie examines the relationship of eugenics and biometry to their
work in mathematical statistics. He shows how Fisher's Genetical
Theory of Natural Selection evidences the eugenics goals which
are usually associated with the older Pearson. While it is a bit trickier
to connect Fisher's books on Scientific Inference and Statistical
Methods to eugenics, MacKenzie is quite convincing.
I
regret not having read this book ten years ago, since it clarified several
issues that I have been struggling with as a teacher of statistics. I looked
it up as a result of a reference in an article by John Aldrich in the journal
Statistical Science (Vol. 10, No. 4, 364-376) on Karl Pearson and
G. U. Yule's views of spurious correlation. Statistical Science,
by the way, often contains interesting articles on the history of statistics.
Abelson
on Statistics as Principled Argument
.
Abelson
is a mathematical psychologist and statistician who, after 40 years of
teaching statistics at Yale, has written a book for his students
to read after they have taken the "normal" statistical curriculum.
His alternative title is "Lots
of things you ought to know about statistics but are too stupefied to ask."He
reflects upon the way traditional statistics instruction (in psychology,
but also in many other disciplines) fails to communicate the ways in which
statistical methodology should serve rhetorical and narrative functions.
Assigning it to you while you are taking this course is too subversive
a thing to do, so I won't, but I will secretly quote some of his insights
now and then. You may enjoy browsing it eventually(!).
It’s $32.50 from amazon.com.
Since
Abelson had been one of the first mathematical social psychologists I read
in the early ‘60s, I was ready to be impressed by his book, and I was.
My latest award for most interesting reflections by a fellow geezer goes
to Howard S. Becker, a sociologist whose 40 year career parallels Abelson’s
in curious ways. Becker, known as a qualitative social researcher, has
written on subjects as apparently diverse as medical education, marijuana
use, and the art world. In this
book he explains what it means to have a sociological perspective on the
world, and why social research is possible.Along the way
he talks about such statistically related topics as random sampling (and
its alternatives), models, causal inference and quotes admiringly several
authorities not usually associated with qualitative social research such
as John Tukey and Paul Lazarsfeld. At amazon.com.
Updated August 16, 2004
Neil W. Henry