Reasoning With Numbers: Estimation, Preference, Feedback, and Policy 
Change
Michael Ranney, Janek Nelson, and Jennifer Garcia de Osuna

Which rate is most/least surprising: the immigration, abortion, inflation,
or murder rate?  What would one prefer such statistics to be, if one
could change them?  Do people care about focused, germane, numerical
feedback that's policy-relevant--e.g., regarding the SAT and admissions
stringency?  How does relative surprise cause people to alter their
understandings and policies?  To what degree does familiarity, confidence,
and caring about a topic modulate these effects?  What reasons do people
voice, and how coherent are folks in such reasoning?

We address such questions by introducing our EPIC Method.  EPIC (roughly)
stands for "Estimate, Prefer, Incorporate-feedback, and Change."  Although
new and novel experimental research, its more proximal methodological
neighbors include empirical procedures and intellectual traditions from:  
judgment and decision making, the cognition of mathematics, science
education, and social psychology.  Our analyses to date have focused most
on the SAT and abortion questions, but we also have results regarding
many issues, such as population changes, higher education, demographics,
the death penalty, etc.  Intriguing factoids and findings will be
provided.