On 20 Sep 2001 11:05:08 -0700, [EMAIL PROTECTED] (Jon Cryer) wrote:
(quoting Robert: even when N=20, a uniform distribution can be treated as
normal for most purposes.)
I assume you meant to say that for N=20, the sample mean based on a random
sample from a uniform distribution can be
Randy Poe wrote:
@Home wrote:
Is there any downloadable freeware that can generate let's say 2000 random
samples of size n=100 from a population of 100 numbers.
Um.
A sample of 100 from a population of 100 is going to
give you the entire population.
Um^2. Only if you sample
In Excel, the random number generator is =RAND()
Produces a number between 0 and 1, inclusive. Some peole dislikie its amount
of randomness, but for class purposes, it seems to work well.
2000 x 100 cells to get your sampel set is going to be big, but I think
do-able.
Or, set up say 100 of
I am interested in the same programs and if possible,
one that can generate normal, binomial, etc distributions
Thanks for any suggestions !!!
_
Prof. J. C. Voltolini
Grupo de Estudos em Ecologia de Mamiferos - ECOMAM
Universidade de
Hi
On Thu, 20 Sep 2001, @Home wrote:
Is there any downloadable freeware that can generate let's say 2000 random
samples of size n=100 from a population of 100 numbers.
Is this conceivable? for excel etc.
Easily done with various statistical software (e.g., SPSS, SAS),
if you have access
A sample of 100 from a population of 100 is going to
give you the entire population
Right my example was flawed, assume n=80 and you run the sampling 1000
times. The random generated list you are sampling has 200 number.
Gus Gassmann [EMAIL PROTECTED] wrote in message
[EMAIL
what about if n is only 15 and the population distribution is heavily
skewed? Isn't there a balancing here. Of course w/81 samples, it is hard to
conceive anything but a normal distrib based on the CLT.
Edward Dreyer [EMAIL PROTECTED] wrote in message
[EMAIL PROTECTED]">news:[EMAIL PROTECTED]...
[ stripping a couple of Newsgroups from the list ]
On Thu, 20 Sep 2001 17:08:42 -0300, Gus Gassmann
[EMAIL PROTECTED] wrote:
Randy Poe wrote:
@Home wrote:
Is there any downloadable freeware that can generate let's say 2000 random
samples of size n=100 from a population of 100
The sample mean is the average of your actual sample
values. It isn't obviously 78 or anything else, though
it might be close to 78. And how did you calculate the standard
error?
I stand corrected on this point. Thanks.
Randy Poe [EMAIL PROTECTED] wrote in message
[EMAIL PROTECTED]">news:[EMAIL
>Subject: WTC 9-11 stats show paranormal connection (Report from Princeton U)
>
>http://noosphere.princeton.edu/
>please read and comment
I'm not surprised by the results. The "materialistic" viewpoint that most extant science still clings to is clearly wrongheaded as shown by quantum physics
I am estimating variance components for a model with heterogeneous
error variances using Gibbs sampling. This is straightforward for
a model where we simply classify records as to which error variance
they represent, sampling from inverse chi-square distributions.
Assuming error variances change
normal populations result in normal sampling distributions of means ... if
one considers all possible samples
non normal populations never result in exactly normal sampling
distributions regardless of sample sizes (though to the naked eye you might
not be able to tell the difference)
the
At 06:28 PM 9/20/01 -0400, Stan Brown wrote:
None that I know, in a formal sense. If you take 100 random samples
of size 81, or 100,000 random samples of size 81, your histogram of
sample means will have the same shape, though the curve will be a
bit smoother with 100,000 samples.
this is for
http://noosphere.princeton.edu/
please read and comment
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Instructions for joining and leaving this list and remarks about
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In article [EMAIL PROTECTED],
Bruce Weaver [EMAIL PROTECTED] wrote:
On 20 Sep 2001, Jay Warner wrote:
true math phobes may not like the idea of putting the equation details
number crunching up to software. the thinking involved in Dennis' list above
is much harder.
Even BC (before
Jon Cryer wrote:
Robert:
even when N=20, a uniform distribution can be treated as
normal for most purposes.
I assume you meant to say that for N=20, the sample mean based on a random
sample from a uniform distribution can be assumed to have a normal
distribution
for most purposes.
I am trying to solve a ? which basically gives the following facts:
population of unknown number
popu std dev of 27
pop mean of 78
sample of size n=81
2000 random samples
The ? is:
what is the sample mean?
what is the std error (std dev of sample means)
what shape would the histogram be?
The
Is there any downloadable freeware that can generate let's say 2000 random
samples of size n=100 from a population of 100 numbers.
Is this conceivable? for excel etc.
=
Instructions for joining and leaving this list and remarks
On Thu, 20 Sep 2001 15:54:24 +0200, JHWB [EMAIL PROTECTED]
wrote:
Hm, hope I didn't make that subject to complex, resulting in zero replies.
But hopefully you can answer this:
I have a N(20,5) distribution and based on that I generated 25 values using
Minitab and the CalcRandom dataNormal
Stan,
Thanks for the detailed explanation. I have one follwoup ?. You say,
If the original population is normally distributed, the sample means
will also be normally distributed. Even if the original population
is skewed, the sample means will still be approximately normally
distributed given
@Home wrote:
I am trying to solve a ? which basically gives the following facts:
population of unknown number
popu std dev of 27
pop mean of 78
With what underlying distribution?
sample of size n=81
2000 random samples
The ? is:
what is the sample mean?
what is the std error
At 05:48 PM 9/20/2001 +, you wrote:
I am trying to solve a ? which basically gives the following facts:
population of unknown number
popu std dev of 27
pop mean of 78
sample of size n=81
2000 random samples
The ? is:
what is the sample mean?
what is the std error (std dev of sample
At 12:27 PM 9/20/2001 -0700, you wrote:
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@Home wrote:
Is there any downloadable freeware that can generate let's say 2000 random
samples of size n=100 from a population of 100 numbers.
Um.
A sample of 100 from a population of 100 is going to
give you the entire population.
- Randy
Would you happen to have the exact location for the expected proportions of
MM colors? I went to the MM site and couldn't seem to locate it.
Rob MacTurk
Paul Bernhardt [EMAIL PROTECTED] wrote in message
[EMAIL PROTECTED]">news:[EMAIL PROTECTED]...
You can have them count the colors of
the level of mathematics
often does not go much beyond cross-multiplying to solve for an unknown,
There's part of the problem in a nutshell. There's no such thing as
cross-multiply. It's..what?..a trick? It epitomizes the shortcut
that hides the rigor behind what's really going on--two
You can have them count the colors of candies in bags of MMs. The MM
web site has the expected proportions published so they can do a
ChiSquare test against those proportions.
Does anybody really care about the proportions of different colors
in bags of MMs?
Do a class of brainstorming to
From an old post...
Plain Peanut
Red 20% 10%
Orange 10% 10%
Yellow 20% 20%
Green 10% 10%
Blue10% 30%
Brown 30% 20%
WBW
E. Jacquelin Dietz wrote:
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Jackie Dietz
Jerry Dallal wrote:
E. Jacquelin Dietz wrote:
We have investigated the possibility of removing attachments from
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Hm, hope I didn't make that subject to complex, resulting in zero replies.
But hopefully you can answer this:
I have a N(20,5) distribution and based on that I generated 25 values using
Minitab and the CalcRandom dataNormal function. The result yielded a mean
of 19,083 and a standard deviation
Rand really doesn't help. You need to put in separate arguments for the
sample size n, number of repetitions,
and location of the population array.
Jay Warner [EMAIL PROTECTED] wrote in message
[EMAIL PROTECTED]">news:[EMAIL PROTECTED]...
In Excel, the random number generator is =RAND()
you may wish to consider NCSS (they have a web site) provides essentially the same
output as SAS but is run from templates not SAS
language. Less expensive, good documentation, excellant support. However does not
provide an audit trail--a necessary feature for
some governmental / legal
- about the citation; and some musing.
On 19 Sep 2001 18:11:59 -0700, [EMAIL PROTECTED] (dennis roberts) wrote:
At 05:14 PM 9/19/01 -0400, Rich Ulrich wrote:
It has Likert's original observations on writing
an attitude scale (1932, which I had not seen elsewhere).
dmr
likert's work
JHWB wrote:
Hm, hope I didn't make that subject to complex, resulting in zero replies.
But hopefully you can answer this:
I have a N(20,5) distribution and based on that I generated 25 values using
Minitab and the CalcRandom dataNormal function. The result yielded a mean
of 19,083 and
Robert:
even when N=20, a uniform distribution can be treated as
normal for most purposes.
I assume you meant to say that for N=20, the sample mean based on a random
sample from a uniform distribution can be assumed to have a normal
distribution
for most purposes.
Right?
Jon Cryer
At 01:16
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