Hi,

Just throwing in my two cents if its helpful. You could potentially wrap the stats functions in a wrapper function to return tidy data but i think `broom`

is probably your best bet at the moment. I have seen several blog posts but nothing as in depth as a book. Im not sure it was mentioned already but i have seen a talk at one of the R conferences that uses a package called `infer`

which might be usefu

When I was first having a look at statistics to see if i could use it for work it basically came down to what i wanted to use it for; it mostly depended on the data, However I found the following books very helpful in general.

Outside of the tidyverse statistical foundations are covered *really* well by Discovering Statistics Using R by Andy Field, Jeremy Miles, Zoe Field. The style is very accessible where each chapter really drives home the conceptual understanding before proceeding to the formulae and assumptions of statistical tests. Its written in a light hearted way and can be read through cover to cover. A similar book which i have not read but is more general and easier is an An Adventure in Statistics: The Reality Enigma. It combines a novel and interweaves the statistical lessons within the novel.

A second book which i cannot recommend highly enough was Statistical Modeling: A Fresh Approach. There are two editions from what i can see but based on the linked one Dr Kaplan spends a lot of setting up why statistical tests are needed. There is a geometry section which draws out why the statistical tests work the way they do. It was the first time i had ever seen anything like this and really gave me a conceptual understanding of the material which up to this point i was just using as a cookbook type thing

Other books I can recommend which don't have anything to do with R would be Statistics in Plain English, Fourth Edition which i didn't read fully but dipped in an out of as a reference and Statistics Done Wrong: The Woefully Complete Guide which I found very witty and chock full of examples of what happens when you ignore assumptions in statistical tests with real world consequences.

If you are on a budget I liked OpenIntro Statistics. The book is free as far as I remember on the open intro website and there is an accompanying coursera course as well (I think). Finally another free book i *really* liked was Learning Statistics with R

I read these books on and off for a couple of years because i was finding the ISLR and ESLR books a bit tough going having not come from a maths background.

I hope this is useful

Thanks