Instructor
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Lee A. Kirkpatrick
office: Millington 249
phone: 221-3997
e-mail: lakirk@wm.edu |
Class Schedule
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Lecture: Tuesdays & Thursdays, 5:00 -
6:20, Millington
123
Lab: Fri. 2:00 - 3:20, Millington 230 (Psychology
library) |
Texts
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1) Howell, David C. (2002). Statistical methods
for psychology
(5th Edition). Belmont, CA: Duxbury. [required]
2) Kirkpatrick, L. A., & Feeney, B. C.
(2005). A simple
guide to SPSS for Windows: For Version 12.0.
Belmont, CA: Wadsworth. [recommended]
Additional readings will be available either on
reserve (at Swem
and/or electronic reserve) or via the WWW.
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Overview and Goals
Course Overview
PSY 631/391 (Advanced Statistics) is designed as the first half of a
two-semester
course sequence, to be followed by PSY 633/392 (Multivariate Analysis)
in the Spring semester. The courses each have two numbers because
they are cross-listed as both graduate (631/633) and advanced
undergraduate
(391/392) courses. Because this year I will be teaching both
courses,
and because I expect the same students to be enrolled both semesters, I
will treat the two courses much like a single two-semester course,
without
worrying much about which material is covered under "Advanced
Statistics"
and which under "Multivariate Analysis." Think of the courses as
"Advanced
Statistics Part 1" and "Advanced Statistics Part 2."
If you don't remember much from your previous statistics
course(s) --
which is typical, actually -- don't panic: We'll be starting more or
less
at the beginning. In many ways this semester will be much like a
(somewhat)
advanced version of an introductory undergraduate statistics course,
covering
the same topics -- e.g., descriptive statistics, t-tests and chi-square
tests, correlation and simple regression, and simple analysis of
variance
-- but in somewhat greater depth. Next semester we will begin with more
advanced topics in analysis of variance, including much that typically
is not covered in an undergraduate statistics course, and then finish
up
with a quick look at a few truly "multivariate" techniques that almost
surely were not covered in your previous undergraduate statistics
course.
The purpose of both of these courses is to prepare students to
analyze
real data from real research, and to understand these analyses at a
conceptual
level. Toward this end, we will focus more on concepts and computer
analyses,
and less on hand calculations and mathematics (particularly next
semester,
when hand calculations become virtually impossible for many of the
advanced
techniques covered). Discussion of issues in research design and
philosophy
of science will be sprinkled throughout the course. I strongly
encourage
you to bring your own statistical questions and problems to class. The
material will make much more sense, and sink in more deeply, when you
think
about it in the context of your own research rather than someone else's
(i.e., your textbook author's and my) examples.
Laboratory
Our laboratory period is scheduled on Friday afternoons from 2:00-3:20,
and we will meet every week unless I announce otherwise. Labs
will
be devoted largely to computer applications (using SPSS for Windows),
review
of homework problems, and discussion of students' own research and
data.
I may also assign additional readings periodically for discussion
during
lab sessions.
We will use SPSS primarily for computer data analysis, and
devote lab
meetings primarily to homework problems, computer applications, and
discussion
of students' research projects.
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Course Requirements and Grades
Grades will computed based primarily on three exams (80%), with the
comprehensive
final exam weighted slightly higher (30%) than the other two (25%
each).
My exams comprise a mixture of computations, interpretation of computer
outputs, and conceptual/short-essay questions. I'll tell you much
more about what to expect as the first exam approaches.
The other 20% of the grade will be based on weekly (more or
less) laboratory/homework
assignments. These assignments typically will involve homework
problems
from the textbook, including both hand and computer (SPSS)
calculations.
Homework problems are not graded for correctness per se, because they
are
intended as practice for exams and not exams themselves. However,
penalties are assessed for incompleteness, tardiness, or clear lack of
reasonable effort.
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