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We generate pairs of properly distributed Gaussian variables at
down to 10nsec intervals, essential in the application. Speed can
be an issue, particularly in real time situations.
Ian
Glen Barnett [EMAIL PROTECTED] wrote in message
a4plof$p3s$[EMAIL PROTECTED]">news:a4plof$p3s$[EMAIL
Hi!
I have 3 random variables i.e. Power (P), Delay (T) and Angle(A). The plot
of P vs T is an exponential shape and the plot of P vs A is a Laplacian
shape. Hence, this implies that the P values are varied with T and A. Hence,
I could not just simply derived the PDF of P by just taking the
In article [EMAIL PROTECTED],
Timothy W. Victor [EMAIL PROTECTED] wrote:
I also think Alan's idea is sound. I start my students off with some
binomial expansion theory.
Giving not the formulas for the standard distributions
but what types of problems result in these is good.
But I believe it
AP wrote:
Hi all:
I would appreciate your help in solving this question.
calculate the standard deviation of a sample where the mean and
standard deviation from the process are provided?
E.g. Process mean = 150; standard deviation = 20. What is the SD for
a sample of 25? The answer
Linda wrote:
I want to generate a series of random variables, X with exponential
PDF with a given mean,MU value. However, I only want X to be in some
specified lower and upper limit?? Say between 0 - 150 i.e. rejected
anything outside this range Does anyone have any ideas how should I do
not to disagree with alan but, my goal was to parallel what glass and
stanley did and that is all ...seems like there are all kinds of
distributions one might discuss AND, there may be more than one order that
is acceptable
most books of recent vintage (and g and s was 1970) don't even
addendum
if one manipulates n and p in a binomial and, gets to a point where a
person would say (or we would say as the instructor) that what you see is
very similar to ... and might even be approximated well by ... the nd
... this MEANS that the nd came first in the sense that one would
Alan Miller wrote (six times):
Linda wrote in message [EMAIL PROTECTED]...
I want to generate a series of random variables, X with exponential
PDF with a given mean,MU value. However, I only want X to be in some
specified lower and upper limit?? Say between 0 - 150 i.e. rejected
anything
At 09:50 AM 2/18/02 +, Ian Buckner wrote:
We generate pairs of properly distributed Gaussian variables at
down to 10nsec intervals, essential in the application. Speed can
be an issue, particularly in real time situations.
Ian
wow ... how our perspectives have changed! back in grad school,
Hello,
I did a likert on 2 groups, a Mann-whitney showed that ther was a
significant difference between the 2 groups. The next thing I did were some
univariate statisics between the covariates and I found some significant
differences between the covariates (ex. age sign. differs between the 2
Are there any Numerical Recipes like textbook on statistics and probability ?
Just wondering..
Thanks.
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Instructions for joining and leaving this list, remarks about the
problem of INAPPROPRIATE MESSAGES, and archives are
what is it you wanted to cook?
At 01:35 PM 2/18/02 -0800, The Truth wrote:
Are there any Numerical Recipes like textbook on statistics and
probability ?
Just wondering..
Thanks.
=
Instructions for joining and leaving this list,
Hi Dennis,
Dennis Roberts wrote:
not to disagree with alan but, my goal was to parallel what glass and
stanley did and that is all ...seems like there are all kinds of
distributions one might discuss AND, there may be more than one order that
is acceptable
Sure, I realised that your goal
The Truth [EMAIL PROTECTED] wrote:
Are there any Numerical Recipes like textbook on statistics and probability ?
I am baffled. Numerical Recipes partly is a book on statistics and
probability. Incidentally:
303778 May 2 1991 ftp://garbo.uwasa.fi/pc/turbopas/nrpas13.zip
nrpas13.zip Numerical
http://www.accessv.com/~joemende/insulin2.gif
Appologies, i also forgot to divide the KCAL in food by the 31 as this
represents kcal. It seems to me logical to advise decreasing food
intake and increasing physical activity to improve insulin
sensitivity. I would probably avoid reporting the
You should take note that R^2 is *not* a very good measure
of 'effect size.'
Hi Rich, you asked to see my data, i've posted the visual at the
following location http://www.accessv.com/~joemende/insulin2.gif note
that the r^2 is low despite the fact that it agrees with common sense:
Insulin
hi,
I'd appreciate an intuitive explanation of the difference between odds
and probabilities.
thanks.
brad
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Instructions for joining and leaving this list, remarks about the
problem of INAPPROPRIATE MESSAGES, and archives are
The Truth wrote:
Are there any Numerical Recipes like textbook on statistics and probability ?
Just wondering..
What do you mean, a book with algorithms for statistics and probability
or a handbook/cookbook list of techniques with some basic explanation?
Glen
Ian Buckner wrote:
We generate pairs of properly distributed Gaussian variables at
down to 10nsec intervals, essential in the application. Speed can
be an issue, particularly in real time situations.
Generated on what? (On a fast enough machine, even clunky old Box-Muller
can probably give
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Abramowitz, Milton and Stegun, Irene A. ,Eds., Handbook of
Mathematical Functions
with Formulas, Graphs and Mathematical Tables, U. S. Gov't. Printing
Office, Wash.
DC Nat. Bureau of Standards., Applied Math Series 55 1964
ASQ has a couple 100 most valuable statistical equations or some
such
The Truth [EMAIL PROTECTED] wrote in message
[EMAIL PROTECTED]">news:[EMAIL PROTECTED]...
Are there any Numerical Recipes like textbook on statistics and
probability ?
Just wondering..
Thanks.
I think one of S-plus manuals, 'statistic with S-plus' comes close in
spirit, though without
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Wuzzy wrote:
http://www.accessv.com/~joemende/insulin2.gif
Appologies, i also forgot to divide the KCAL in food by the 31 as this
represents kcal. It seems to me logical to advise decreasing food
intake and increasing physical activity to improve insulin
sensitivity. I would probably
Odd is defined to be
P(event)
---
1- P(event)
So if P(event) is 0.50, then the odd is 1 to 1. If P(event) is 0.75, then the
odd is 3 to 1 since 0.75 is three times as large as 1 - 0.75 = 0.25.
Given one of odds or probabilities, you can always derive the other.
Ken
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