Principled statistical inference in data science
TA Kuffner, GA Young - Statistical Data Science, 2018 - World Scientific
Statistical Data Science, 2018•World Scientific
… We discuss the challenges of principled statistical inference in modern data science.
Conditionality principles are argued as key to achieving valid statistical inference, in particular
when this is performed after selecting a model from sample data itself. … We argue that a
principled approach to inference in the data science context is essential, to avoid erroneous
conclusions, in particular invalid statements about significance. We will be concerned here with …
Conditionality principles are argued as key to achieving valid statistical inference, in particular
when this is performed after selecting a model from sample data itself. … We argue that a
principled approach to inference in the data science context is essential, to avoid erroneous
conclusions, in particular invalid statements about significance. We will be concerned here with …
We discuss the challenges of principled statistical inference in modern data science. Conditionality principles are argued as key to achieving valid statistical inference, in particular when this is performed after selecting a model from sample data itself.
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