Interpretive tips for understanding science
From David Spiegelhalter, William Sutherland, and Mark Burgman, twenty (mostly statistical) tips for interpreting scientific findings
To this end, we suggest 20 concepts that should be part of the education of civil servants, politicians, policy advisers and journalists — and anyone else who may have to interact with science or scientists. Politicians with a healthy scepticism of scientific advocates might simply prefer to arm themselves with this critical set of knowledge.
A few of the tips, without their detailed explication:
- Differences and chance cause variation
- No measurement is exact
- Bigger is usually better for sample size
- Controls are important
- Beware the base-rate fallacy
- Feelings influence risk perception
Thomas Lumley (@tslumley) is Professor of Biostatistics at the University of Auckland. His research interests include semiparametric models, survey sampling, statistical computing, foundations of statistics, and whatever methodological problems his medical collaborators come up with. He also blogs at Biased and Inefficient See all posts by Thomas Lumley »
“Extrapolating beyond the data is risky.”
https://bobbiblogger.files.wordpress.com/2012/03/extrapolate.jpg
This is a really fascinating one. Obviously you can’t often extrapolate something with certainty, and we can all think of examples of bad, failing extrapolations.
On the other hand, pretty much whenever you believe anything (e.g. I will not float up into space in the next two minutes), it implies an extrapolation that is not deductively justified . And it’s just as much a mistake to doubt these as it is to believe one of Randall Monroe’s extrapolations.
There’s a really good discussion of this (and Occam’s razor etc) in one of Harold Jeffreys’s books, I forget which one.
11 years ago