Re: Meaning of Zero and All, Application to archaeology

From: Eric Stevens (eric.stevens_at_sum.co.nz)
Date: 01/20/05 

Date: Fri, 21 Jan 2005 10:09:50 +1300

On Thu, 20 Jan 2005 20:14:03 GMT, Philip Deitiker
<Donevenask@worlnet.att.net> wrote:

>I know that Alan was Joking, apparently Steve didn't catch on.
>But on a more serious note. This is in response to Doug's reply
>
>"
>I've never understood that 'old dictum'.
>Absence of evidence is in fact evidence of absence. Not proof, but
>evidence of the probability of absence. And how likely that is
>depends upon the context.

The old dictum in fact is "Absence of evidence is NOT evidence of
absence" though many would argue that it was.
>"

  --- lengthy exposition snipped ----
>
>Thus when a person declares Zero frequency of an event based on zero
>events he is also saying that the sampling for (not of) such events
>was great, that biasing or sampling errors is not a factor worthy of
>affecting the conclusion. And when a person says that a zero events
>does not reflect the reality or possibilities he is saying that
>sampling is poor, or the sampling was biased or that there were
>sampling errors to a degree in which a zero frequency conclusion
>should not be drawn. He is also saying, implicitly saying that
>because he knows that the zero result in terms of binomial
>probability opens the possibility for an infinite number events of
>non-zero frequency, that he has some trend that approaches with non-
>zero result the parameter proximal to where the sampling
>result/parameter crosses the Y=0 axis. If we hold every argument to
>this standard of plausibility then many arguments will be summarily
>eliminated, sort of a kook filter, right off the bat. Does this
>argument mean something to the individual, or is it something they
>must ignore because they don't understand it.
>

It's probably simpler for the ordinary individual to say 'the reason
you have no evidence is that you haven't found it yet'. :-)

Of course this opens up the argument of whether or not there is any to
find. You cannot strictly apply your binomial analysis until you know
something about the larger distribution. i.e. - does it exist?

Eric Stevens

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