Miguel,

Here's a link to my stat syllabus. I do need to point out that, while my
syllabus says that I covered factorial ANOVA, I ended up having to skip
it in order to cover techniques for nominal and ordinal data. Hope this
helps your project.

http://www.shepherd.edu/psychweb/syllabi/PSYC250_Daily.pdf

Larry 

-----Original Message-----
From: Miguel Roig [mailto:[EMAIL PROTECTED] 
Sent: Sunday, June 17, 2007 6:17 PM
To: Teaching in the Psychological Sciences (TIPS)
Subject: [tips] Knowledge of statistics in our best students

Tipsters, over the years, I have reviewed a number of papers that are
submitted to local and national conferences, as well as to other outlets
of student research (e.g., student journals, competitive awards). In
many cases you can 'hear' the student 'voice' in their writing with
respect to the various stock phrases (e.g., "many experiments show
..."), inappropriate use of terms (e.g., utilize, prove) that we often
find in student papers. You also get a general idea that the paper is,
indeed, the student's own research by, for example, the type of topic
chosen (e.g., eating disorders is a fairly popular one), the general
design of the study, and even in type of the data analyses used (e.g.,
correlations, t-tests simple ANOVAs). In sum, in those cases I have no
doubts that the project was the students' own even if I suspect that the
student has received considerable assistance from a mentor. However, in
other cases, a student submission is written at a professional or
near-professional level, the literature review shows a fairly thorough
grasp of relevant issues, and the data are analyzed with fairly
sophisticated statistical techniques (e.g., hierarchal regression,
MANOVAs, ANCOVAS, structural equations). Some of these papers are of
such high quality that, frankly, one begins to wonder the extent of the
student's contribution to the paper.

I actually have some evidence indicating that some students are given
unmerited authorship (see
http://facpub.stjohns.edu/%7Eroigm/presentations/student%20authorship%20
in%2
0EPA%2006.ppt). However, it is with respect to students' knowledge of
advanced statistical techniques that I now want to pick your brains. So,
here are my questions for the group: What are the most advanced data
analysis techniques that you are covered in the Statistics course
offered in your department? Does your department offer an advanced
statistics course and what areas do you cover in those courses? For both
questions, a link to a syllabus or course description will be
sufficient.

TIA

Miguel



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