Re: Attention Sean - question about CSI

On Aug 2, 5:56 pm, hersheyh <hershe...@xxxxxxxxx> wrote:
On Aug 2, 6:01 pm, Seanpit <seanpitnos...@xxxxxxxxxxxxxxxxxxxxxxxxxxx>

Using your formula, would you be able to determine that one was
"intelligently designed" and the other was "randomly generated"?

As I've said over and over again, CSI does not equal ETI or ID. All
that the detection of high CSI indicates is likely non-random bias.

And what, exactly do you mean by "non-random bias"?

This is like explaining the definition of "is" to former Pres.
Clinton.

In short, if a string is algorithmically random, it is not predictable
or compressible with a smaller algorithm than the string itself.
Therefore a biased non-random string is both predictable and
compressible with use of a smaller algorithm.

What probability
level are you using and how did you determine it? Especialy given
that the same CSI number can either indicate a sequence very close to
the reference sequence or one that is very far away. We are not
interested in a two-tailed test here. And wouldn't using a sd of the
distribution of sequences relative to the reference be a better way to
do that?

You should be interested in a two-tailed test. Obviously, if a
sequence is the exact opposite of a given string, such a perfect
negative image would be just as unlikely to be the result of random
generation as a perfect positive image copy.

You can use standard deviation if you want. The final result will be
the same. Those strings with higher CSI have better odds of non-
random biased production corresponding in degree compared to those
with lower CSI values.

In this case, since your two sequences have very high CSI relative to
each other, one or the other or both most likely had a biased non-
random origin.

The CSI for the two sequences is that for identical copies; you know
the CSI for each sequence to the same reference sequence. The
question is, how does that number represent anything that could
possibly be called CSI?

If you had actually read what I wrote in the post to which you just
responded, you'd know that the reference for each string in this
scenario is the other string.

I never said that my CSI formula detects ETI or ID. It doesn't. It
only detects bias. How many times do I have to point this out to you
before it sinks in?

It doesn't (as far as I can tell) even detect bias, which remains
undefined.

If you'd read up a little on the concept of algorithmic randomness,
you'd see that these concepts are defined.

Sean Pitman
www.DetectingDesign.com

.

Relevant Pages

  • Re: The Revised Pitman CSI Formula
    ... arbitrary choice of 'reference' sequence. ... My formula for detecting high levels of CSI does not involve the ... not known by comparing it to a reference string that is known. ...
    (talk.origins)
  • Re: The Pitman CSI Formula
    ... Complex Specified Information (CSI). ... Given a string A and a reference string B ... sequence of length x in a long series of single letter changes, ...
    (talk.origins)
  • Re: Measuring CSI
    ... mathematical formula for converting a sequence of symbols to a complexity ... the universe that contains a particular pattern or sequence. ... doesn't really matter what a string or pattern looks like. ... turn into a CSI number. ...
    (talk.origins)
  • Re: Coin tossing guessing strategy...
    ... ANY *particular* string, such as HTTHHHTHTHTT has the same probability ... How would a coin even know whether it came up H or T? ... with respect to sequences of n flips, is to note that if some sequence ... it's not reasonable to claim the bias happens ...
    (sci.math)
  • Re: Measuring CSI
    ... size of sequence space. ... string of digits of p is not random and its Kolmogorov complexity rate ... you using one to compute CSI or not? ...
    (talk.origins)