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