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STAT 502
Experimental Statistics II
Purpose:
This course will cover various topics in multiple regression analysis, analysis of variance,
and experimental design.
Prerequisite: Stat 502 assumes a background in basic data analysis and statistical
inference: at least the equivalent of Stat 501.
My take:
I think most of the concepts and procedures in Stat 502 are not too difficult, but some of
them are certainly challenging and will take time to fully learn and understand them well.
Many of
you will find the basic concepts somewhat easy to understand but have a very difficult time when you
sit down to actually produce the required work, be it homework calculations and/or SAS output.
My
suggestion is to stick with it and start your homeworks early!
The nature of STAT 502 requires that you understand material well to build upon for later
topics, it literally is like constructing a house and at anytime if you fall behind you will find the
material very foreign if understandable at all so keep up!
Regarding SAS, if you feel you shouldn’t be required to learn SAS in STAT 502, the
individuals that need to hear this are NOT in the STAT department.
They are those that are
responsible for determining that you take STAT 502 (IE Who told you to take 502?). Some
departments offer alternate courses, as far as the STAT department is concerned 502 will be taught
using SAS (See
Computing
below).
Instructor:
Tadd Colver
Office: MATH 507
Phone: 7654940030
Email:
colvertn@stat.purdue.edu
Office hours:
TBA or by appointment—if for any reason you need to see me outside
regular office hours, please email me and I’ll try to accommodate you
Text:
Kleinbaum, David G. et. al. Applied Regression Analysis and Other Multivariate Methods, 4th
edition.
Duxbury Press, 2008. (ISBN 0495384968)
You are encouraged to review material from the book prior to our discussing it in class.
I don’t
expect you to teach yourself the material but in almost all cases, you will understand my
lectures much better having seen the material beforehand.
Attendance:
Although class attendance is never mandatory, you are required to complete all course
assignments on time regardless of absence, as all late work will be given zero credit.
This is especially
true for exams, you
MUST ATTEND all scheduled exams
, including the final exam, at the scheduled
time.
If your schedule will not permit that during this semester then I suggest you take the course
during a different semester.
As you get to know my teaching style, you will find that I teach highly conceptually, and
therefore class attendance, and participation in class, is strongly encouraged.
In class, feel free to come
and go as needed but do not interrupt the flow of the lecture or you will politely be asked to leave.
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View Full DocumentCommunication:
I expect the same communication you expect from me.
If I were to change an
assignment, I would think you would want to know about the change BEFORE the due date. Well then
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 Spring '08
 Staff
 Statistics, Regression Analysis, Variance

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