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
Bill said earlier:
>> Yes, we do this so that we will have examples of all combinations of x1
and
>> x2,as we would do when using a factorial anova design. But such uniform
>> sampling does not make the variables into causes, Adding x1 to x2 causes
y,
>
Gus responded:
>Here you are using a ver
William Chambers wrote:
>
> Guss said:
> >
> >No. You said yourself that you are _selecting_ the x1 and x2 to be
> >uniform.
>
> Yes, we do this so that we will have examples of all combinations of x1 and
> x2,as we would do when using a factorial anova design. But such uniform
> sampling does
Guss said:
>
>No. You said yourself that you are _selecting_ the x1 and x2 to be
>uniform.
Yes, we do this so that we will have examples of all combinations of x1 and
x2,as we would do when using a factorial anova design. But such uniform
sampling does not make the variables into causes, Addin
William Chambers wrote:
>
> Gus said:
>
> >Here is how I interpret what you've said to date:
>
> >1. If you take two uniformly distributed random variables x1 and x2 and
> >form
> > the sum y = x1 + x2, then y has a distribution that is not uniform.
> >2. If you have two variables x and y and
Gus said:
>Here is how I interpret what you've said to date:
>1. If you take two uniformly distributed random variables x1 and x2 and
>form
> the sum y = x1 + x2, then y has a distribution that is not uniform.
>2. If you have two variables x and y and want to determine whether x
>depends
> o
William Chambers wrote:
>
> Gus,
>
> You are making a defense of studying distributions as they are thrown at us
> by nature/circumstances, This seem the way to go to social scientists
> because we tend to believe that our causes are embedded in all sorts of
> complex interactions and can not b
Gottfried said:
>
>Here you focus the crux of the normal-distributed variables.
>If there is a reality with n1 and n2 as normal distributed causes and
>y as effect like y<-n1+n2, you have measured standardized z1 and z2 (not
knowing
>which represents y and which represents n1 of the model)
>then y
Gus,
You are making a defense of studying distributions as they are thrown at us
by nature/circumstances, This seem the way to go to social scientists
because we tend to believe that our causes are embedded in all sorts of
complex interactions and can not be isolated from their context, If we l
On 10 Feb 2000, Richard M. Barton wrote:
> --- Alex Yu wrote:
>
> A statistical procedure alone cannot determine casual relationships.
> ---
>
>
> Correct. A lot depends on eye contact.
>
> rb
And also, at least 2 statistical procedures are required...
=
sofyan2000 wrote:
>
> Is there a statistical test in ANOVA / MANOVA that can show the causal
> direction between 2 variables (Independent and Dependent).
In short, no.
In more detail, causal inference is dependent on the design you used,
not
the statistical technique applied to the data. If yo
--- Alex Yu wrote:
A statistical procedure alone cannot determine casual relationships.
---
Correct. A lot depends on eye contact.
rb
===
This list is open to everyone. Occasionally, people lacking respect
for othe
A statistical procedure alone cannot determine casual relationships.
Rather it involves the design and measurement issues. The following is
extracted from my handout:
One of the objectives of conducting experiments is to make causal
inferences. At least three criteria need to be fulfilled to
At 12:40 PM 2/10/00 +, sofyan2000 wrote:
>Is there a statistical test in ANOVA / MANOVA that can show the causal
>direction between 2 variables (Independent and Dependent).
i don't think so ... this is determined (if it can be at all) by the DESIGN
of the investigation ... and what you did wh
Is there a statistical test in ANOVA / MANOVA that can show the causal
direction between 2 variables (Independent and Dependent).
===
This list is open to everyone. Occasionally, people lacking respect
for other member
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