Re: Cluster analysis for beginners

On Mar 30, 1:36 am, Jerry Dallal <gdal...@xxxxxxxxxxxxxxxxxxxx> wrote:
illywhacker wrote:
On Mar 29, 4:38 pm, David Winsemius <doe_s...@xxxxxxxxxxx> wrote:
Sidney <milan_y...@xxxxxx> wrote innews:24466740.1175159875339.JavaMail.jakarta@xxxxxxxxxxxxxxxxxxxxxx:

1) Classical hypothesis testing is fatally flawed. No well-defined
alternative is specified, and the probability of the data is not
calculated. Rather the probability of a set of unobserved data points
is
calculated. As Jeffreys famously put it: "A hypothesis that may be
true may
be rejected because it has not predicted observable results that have
not
occurred". There is a mass of literature on this.

This is a "joke", of course, that results from thinking of P values as
posterior probabilities. If P values are thought of in terms of fixed
level tests, Jeffreys' comment makes no sense.

As I believe someone has replied to you before now: calling it a
'joke' may save you the trouble of bothering to think too hard about
its implications for your practice, but it does not, alas, remove the
force of the remark.

Hypothesis testing without an alternative will always be flawed,
because there is always at least one model that predicts the data (or
the sets of unobserved data that classical hypothesis testing likes to
calculate with) with certainty, and which will therefore always be
better than any other hypothesis. Why should we discard this model?
Prior knowledge of course. And if prior knowledge about this model,
why not others? And now the whole thing is up in the air.

Asking whether the clusters are "significant" is too vague to answer. I
suspect what the OP meant was whether the clusters are "remarkable".

This is a joke too right? You are replacing one undefined word with
another. This is indeed both remarkable and significant.

illywhacker;

.