Why is it wise for a researcher to report the effect size in addition to statistical significance? How do you explain it?

Rarnold

The two  concepts are
different, effect size estimates the impact on an intervention, significance idicates
the likleyhood that the impact is due to chance or random
effects.

You can have a very big effect, that is a fluke,
or random variation, or you can have a very small effect size that is highly unlikly to
be due to chance, and every thing in between.

In clinical
work we like to have statistical significance (not due to chance)
and clinical significance (the effect is big enough to be noticable and
make a difference to a patient).  A simple effect size calculation is to subtract the
control (or before score) group overall score from the intervention group (or after
score) overall score and divide by the standard deviation of the control
group.

What is a good effect size?  Depends a quite a few
elements--but a rule of thumb is less than 0.5 small, up to 0.8 medium and over is
large--but these are critisesed as being  'T shirt effect
sizes'

Another important consideration is Confidence
Intervals--these indicate the range of possible scores your result lies
within

Silverstrummer