In which I side with Neyman over Fisher
Statistical Modeling, Causal Inference, and Social Science 2013-05-24
Summary:
As a data analyst and a scientist, Fisher > Neyman, no question. But as a theorist, Fisher came up with ideas that worked just fine in his applications but can fall apart when people try to apply them too generally. Here’s an example that recently came up. Deborah Mayo pointed me to a comment by [...]
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