In generall Draw a random number from a uniform (0,1) distribution and
invert the CDF to solve for the value of x such
that F(x)=rand. Quicker techniques work for known distributions.
Alejandra Mercado <[EMAIL PROTECTED]> wrote in message
89jmg3$qpt$[EMAIL PROTECTED]">news:89jmg3$qpt$[EMAIL PROTE
~~
BEYOND THE FORMULA IV
~~
A Statistics Conference for Mathematics Teachers
Teaching Introductory Statistics
DATE:
Thursday, August 3, 2000,
8:30 AM to 4:30 PM
6:30 PM to 9:00
Hi,
The subject title may be a little extreme, but I do wish to get your
attention and ask for your feedback.
I am doing research for my company in the area of college and
university textbook publishing, specifically to understand the
economics and market for professors and departments wishing
William and Gus:
Please excuse a lurker for stepping in here, I've been following this
thread for several days and would like to add something. Perhaps
something that has been said already.
Proving causality from a correlation algorithm would be wonderful, but
I don't think it
In article <89jmg3$qpt$[EMAIL PROTECTED]>,
Alejandra Mercado <[EMAIL PROTECTED]> wrote:
>I need to generate random vectors
>with a specified distribution.
>Does anyone know what's a good
>reference for this?
A book which covers a large variety of distributions,
as well as general methods, is the
In my experience Hosmer and Lemeshow is the best intro, although it is not
a perfect book for all users. One limitation/strength (depending on your
perspective) is that it is oriented towards the biomedical sciences.
On Thu, 2 Mar 2000 [EMAIL PROTECTED] wrote:
> I want to buy an intro. book on
On 28 Feb 2000 10:54:11 -0800, [EMAIL PROTECTED] (Alan
Neustadtl) wrote:
>I agree with Dennis Roberts sentiment that:
>
>>
>>what seems like a simple notion is very complicated
>>
>
>This issue is being actively discussed and analyzed by people in AAPOR,
>the American Association of Public Opinio
I agree with Scott Millis about J. Scott Long's book "Regression Models for
Categorical and
Limited Dependent Variables." Quite comprehensive, good examples, well
written, reasonably priced.
Steve DesJardins
Stephen L. DesJardins
Planning, Policy, and Leadership Studies
University of Iowa
N491
For the design of the study a good early introduction is "Conducting
Meaningful Experiments" By Bausell, Sage Publications. It emphasizes a
lot of the activities that should take place before any data is collected
with a focus on forming meaning hypotheses. It also includes an overview
on good
I'd suggest J. Scott Long's book, Regression Models for Categorical and
Limited Dependent Variables, as well as Scott Menard's Applied Logistic
Regression Analysis. From a Bayesian perspective, "Ordinal data
modeling," by Valen Johnson and James Albert is excellent.
Scott Millis
[EMAIL PROTECTE
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