As long as Ken asked me to share my experience with 3-days course SAS Statistics I : introduction to ANOVA, Regression and Logistic Regression , I am doing it now.
First of all, I am very happy that I took this course although in some extent, David was right regarding the lack of statistical basics for this class. Should I have more basic statistical background I would have gain more knowledge than I did .It was not easy for me to follow the lecture and while my classmates did not bring our nice (and heavy) textbook at home every day, I had to do it for all three days to re-read all staffL. That was my homework that I assigned to myself...
Fortunately our 11 students group was pretty homogeneous and just 2 of us had kind of statistical background (one of those two lacked SAS skills however).Therefore my naïve questions to instructor did not ruin others’ training and sometimes even matched others’ unspoken questions (as I was said during the lunch)
On the other hand, none of my classmates ever handled with Non-parametric way in ANOVA (while I did it once!) and just one of them handled with Factor Analysis (while I happened to handle it once-a little bitJ ). However, our instructor did not described it in deep as both these topics were rather subjects for Appendix in our text book
The most important thing for me was that our instructor tried to interpret proc outputs for us. We did exercises after each chapter. Therefore those of us who were slow just had to finish doing it during coffee breaksJ
Our instructor was able to cover the following staff:
Introduction to Statistics
ANOVA
Regression
Regression Diagnostics
Categorical Data Analysis
As well as some of Appendix material:
Additional Topics (paired t-tests; two sample t-tests, Non-parametric ANOVA)
Now I have a feeling that I have to read all staff again and definitely, it should help me in my work.
Hopefully my description above will be helpful to somebody who is going to take this course.
Irin
Kevin Roland Viel <kviel@EMORY.EDU> wrote: On Mon, 22 May 2006, Irin later wrote:
> Hi experts!
> Tomorrow I am going to take a 3 days Statistics I course: Introduction to ANOVA, REGRESSION, and Logistic Regression with SAS Institute
>
> Prerequisites require some SAS skills as well as ….. an undergraduate
> course in statistics covering p-values, hypothesis testing, analysis
> of variance, and regression.
>
> While I have some SAS skills and used some statistical PROCs in SAS,
> I never took any undergraduate course in statistics. Instead I tried
> to compensate it with an extensive reading for about a month time
> period. However today, reviewing what I already read ABOUT analysis of
> variance, I found out that unlike p-value concept I do not understand
> clearly what is F concept as well as F-value and F-value ratio. What I
> got from the reading is that F-value is rather a result of a
> distribution and then after I get F-value, I can produce P-value.
> Does it mean that in some cases one can produce p-value without F value while in some cases it is not like that? If my assumption is correct then …in which cases it is needed ?
> So…I feel a little bit nervous for tomorrow….Could anybody give me a short and simple explanation of the concept?
> Any help would be greatly appreciated!!!
Irin,
It seems that you might be at a minor disadvantage. You will take away
the course notes, but always extensively network. Get as many addresses
or business cards as possible. Find out who in the class has an interests
in your substantive field(s).
The course may only be three days, but SAS-L is always here.
For the long term, let me recommend three books, with the disclaimer
that the some of the authors of the first two are professors with my
school:
1) Applied Linear Statistical Models with Student CD (Hardcover)
by Michael H Kutner et al.
http://www.amazon.com/gp/product/007...lance&n=283155
2) Applied Regression Analysis and Multivariable Methods (Hardcover)
by David G. Kleinbaum et al.
http://www.amazon.com/gp/product/053...lance&n=283155
3) Mathematical Statistics with Applications (Mathematical Statistics (W/
Applications)) by Dennis Wackerly et al.
http://www.amazon.com/gp/product/053...lance&n=283155
A note on 3) Wackerly and Mendelhall switch authorship positions with
different versions.
I would take 2) as the optional book, but a definite addition to the
second level of your library. David et al. address some important issue
that I have not seen elsewhere. In addition, David has written texts on
logistic and survival analyses for a very general audience. You should at
least visit the library to see if these texts are not suited to your
taste.
As far as getting you running, 1) is your book, whether or not you have a
background in statistics and matrices or not.
I feel that the presentations of statistics should begin with the
theoretical. When you understand what a statistic is and the various
criteria (consistency, minimum variance, etc.) their application becomes
much less arcane.
I am sure that I have not helped you too much, but more competent
statisticians on this list are sure to explain much more accurately and
concisely, so keep looking.
Good luck and let us know how you liked the class,
Kevin
Kevin Viel
Department of Epidemiology
Rollins School of Public Health
Emory University
Atlanta, GA 30322
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