[EMAIL PROTECTED] (Jay Warner) wrote in news:[EMAIL PROTECTED]:

> "correlation" says that when we observe a change in one variable, we
> see a consistent change in the other.  If the correlation is positive,
> then both go up together and down together.  If the correlation is
> negative, then as one goes up, the other goes down, and vice versa.

Not quite.  Correlation specifically implies that the average of one 
variable is proportional to the value of the other.  There are 
relationships that meet your definition but show little correlation.

> 
> "dependence"  indicates that variable B is controlled, or is caused
> by, variable A.  the question of what is 'causality' takes up more
> space than the internet has available.

Specifically, dependence means that if you know the value of B, you can 
make a better guess at the value of A than if you didn't.

> In Box, Hunter & Hunter is a plot of the human population of
> Oldenberg, Germany, against the number of nesting storks for a certain
> time period.  It "proves" that storks bring human babies, since more
> storks means more people. Does the human population "depend" on the
> stork population?  I don't think so.  Is the human population
> correlated with the stork population?  Yup. 

But technically, that *is* a relationship of dependence.  Knowing the stork 
population helps you estimate the human population.  That in no way implies 
any sort of causal relationship; all it implies is that the joint 
distribution of human population and stork population isn't the same for 
different marginal values of stork populations.  Dependence != causality.
Dependence is not an inherently asymmetric relationship.
.
.
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