Re: Science = 100% falsifiability? Really?

On Dec 12, 3:43 pm, Free Lunch <lu...@xxxxxxxxxxxxxx> wrote:
On Wed, 12 Dec 2007 15:18:20 -0800 (PST), in talk.origins
Seanpit <seanpitnos...@xxxxxxxxxxxxxxxxxxxxxxxxxxx> wrote in
<d1c84026-d730-4983-88cf-44285a845...@xxxxxxxxxxxxxxxxxxxxxxxxxxxx>:

On Dec 12, 11:43 am, richardalanforr...@xxxxxxxxxxxxxx wrote:

Of course, I know perfectly well that you won't, because you know
perfectly well that your arguments have no substance, and that any
competent scientist would laugh them out of court.

What would be laughed at of court, even by mainstream scientists, is
your notion that all real scientific theories are absolutely
falsifiable. That notion shows a very basic misunderstanding of the
uses and range of scientific investigation.

Apparently you do not grasp the meaning of falsifiable. Which scientific
theories are not?

Apparently you do not grasp the meaning of the term absolutely
falsifiable. Many very useful scientific hypotheses and theories are
not absolutely falsifiable.

Let's all have a good laugh as you bluster and evade once again. What
sort of impression do you think that this gives, do you think?

Let see you explain how medical science isn't really science . . .
because the majority of medical hypotheses and theories are not
absolutely falsifiable you know. The same thing is true of physics,
chemistry, anthropology . . . even mathematics.

Medicine is poorly managed because it seldom has proper double-blind
studies. I have no idea how you would do a double-blind study on the
efficacy of surgery for lower-back pain.

Double-blinded studies do not usually have the power to *absolutely*
falsify the null hypothesis. They have the power to make the null
hypothesis unlikely, but not to falsify it to 100% certainty. Richard
suggests that all true scientific hypotheses must have the potential
to be absolutely falsified. In reality, most scientific hypotheses
cannot be absolutely falsified, but only falsified by a certain degree
of pre-determined statistical "significance". That is why concepts
like p-values come into play in many forms of scientific
investigation.

Sean Pitman
www.DetectingDesign.com

.

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