On Wednesday, 8 March 2017 at 14:02:40 UTC, Moritz Maxeiner wrote:
On Wednesday, 8 March 2017 at 13:14:19 UTC, XavierAP wrote:
On Wednesday, 8 March 2017 at 12:42:37 UTC, Moritz Maxeiner
wrote:
On Tuesday, 7 March 2017 at 22:07:51 UTC, XavierAP wrote:
Plus statistics can prove nothing -- this logical truth
cannot be overstated.
It's called empirical evidence and it's one of the most
important techniques in science[2] to create foundation for a
hypothesis.
No, mistaking historical data as empirically valid is the most
dangerous scientific mistake. The empirical method requires
all conditions to be controlled, in order for factors to be
isolated, and every experiment to be reproducible.
This is true for controlled experiments like the one I pointed
to and this model works fine for those sciences where
controlled experiments are applicable (e.g. physics).
For (soft) sciences where human behaviour is a factor - and it
usually is one you cannot reliably control - using
quasi-experiments with a high sample size is a generally
accepted practice to accumulate empirical data.
Right, but that's why "soft" sciences that use any "soft" version
of the empirical method, have no true claim to being actual
sciences. And it's why whenever you don't like an economist's
opinion, you can easily find another with the opposite opinion
and his own model.
There are other sane approaches for "soft" sciences where
(controlled) experiments aren't possible:
https://en.wikipedia.org/wiki/Praxeology#Origin_and_etymology
Of course these methods have limits on what can be inferred,
whereas with models tuned onto garbage historical statistics you
can keep publishing to scientific journals forever, and never
reach any incontestable conclusion.
