It’s always important to keep that in mind and to not overestimate what our models actually say.

"If I can't picture it, I can't understand it."

Below is a link to a great article on the science of statistics by George E. P. Box, where he mentions, and develops, his famous dictum that “all models are wrong” (qualifying it with the fact of their usefulness – “all models are wrong, but some are useful”, though this does not appear in the article varbatim)

Drawing examples from the work of another famous statistician, R.A. Fisher, George Box includes valuable lessons for data analysts (as relevant today as back then), such as:bimodal

  • the importance of focusing on both theory and practice in statistical work, especially academic
  • the ability to “devise simple but evocative models”
  • not falling in love with your models (borrowing the metaphor of Pygmalion from Francis Bacon)
  • resisting the temptations of “cookbookery” and “mathematistry”

Box first talks about the scientific method as a continual iteration between theory and practice (deduction and induction), and then illustrates this…

View original post 217 more words

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