Translate to multiple languages

Subscribe to my Email updates
Enjoy what you've read, make sure you subscribe to my Email Updates

Tuesday, December 18, 2018

Statistical Inference as Severe Testing - How to Get Beyond the Statistics Wars | Cambridge University Press

Follow on Twitter as @learnfromerror
Check out How to Get Beyond the Statistics Wars by Deborah G. Mayo, Professor Emerita in the Department of Philosophy at Virginia Tech.  

Statistical Inference as Severe Testing
How to Get Beyond the Statistics Wars
It is easy to lie with statistics . Or so the cliché goes. It is also very difficult to uncover these lies without statistical methods–at least of the right kind. Self-correcting statistical methods are needed, and, with minimal technical fanfare, that’s what I aim to illuminate.

Mounting failures of replication in social and biological sciences give a new urgency to critically appraising proposed reforms. This book pulls back the cover on disagreements between experts charged with restoring integrity to science. It denies two pervasive views of the role of probability in inference: to assign degrees of belief, and to control error rates in a long run. If statistical consumers are unaware of assumptions behind rival evidence reforms, they can't scrutinize the consequences that affect them (in personalized medicine, psychology, etc.). The book sets sail with a simple tool: if little has been done to rule out flaws in inferring a claim, then it has not passed a severe test...

Philosophical tools are put to work to solve problems about science and pseudoscience, induction and falsification.
  • Views a contentious debate as a difference in goals to enable fair-minded engagement
  • Refocuses on the goal of learning from error to shed fresh light on statistical inference
  • Offers a bridge between long-standing philosophical problems and concerns of practicing scientists and statisticians
Read more... 

Source: Cambridge University Press