> Unfortunately, the resources I've found have left much to be desired. Yeah most textbooks out there are pretty bad (aim to cover the standard curriculum, whi

> Unfortunately, the resources I've found have left much to be desired. Yeah most textbooks out there are pretty bad (aim to cover the standard curriculum, which is not very useful for most practical statistical analysis tasks). Recently however, there has been a growing number of teachers/educators adopting the "modern statistics curriculum" based on resampling methods (bootstrap estimation and permutation tests), so you should look for those if you want a review that is more friendly to learners with a coding background. I have another google doc where I've saved the best links to learning resources, you might want to check out while waiting for the book (it might take a while!): https://docs.google.com/document/d/1GWyuNC4qCL5ecYSoY6GxvuhOz4AxYEhIKzSS_lgEGaY/edit# https://docs.google.com/document/d/1GWyuNC4qCL5ecYSoY6GxvuhO... In particular the talks by Vanderplas and Downey in the section "Tutorials > Resampling methods" are all excellent. Also, here is a four-part video tutorial + notebooks that I prepared, which gives an overview of all parts of modern curriculum (from data management, through prob theory, to stats modelling): https://nobsstats.com/stats_overview/README.html https://nobsstats.com/stats_overview/README.html