I like Alan Downeys books Think Stats, Think Bayes. He introduces topics in Statistics using python:

https://greenteapress.com/wp/think-stats-2e/ https://greenteapress.com/wp/think-bayes/

I worked through think stats a couple of years ago. But I was lost on where to go next. It seems like there’s a gap between textbook and working world stats.

I wanted things like design of experiments and hierarchical bayes methods, logistic regressions, and other somewhat advanced topics, and most of the things I found were poorly written R documentation. Which from a development perspective is too much effort to grok, read papers, and then port the code to python.

It really sucks that R is the go to for so much when deploying R in a production environment is a pain or not possible.

It depends how comfortable you are with mathematics. Statistics by David Freedman is a great starting point and does an excellent job of developing intuition without delving deep into the mathematical aspects. Although it may leave you wanting more details on the math side. Another great book for beginners is Statistics: The Art and Science of Learning from Data by Agresti and Franklin.

In any case, I would recommend skimming a lot of books and finding one that contains enough practice questions (with solutions) and is suitable for your level.

For beginners, "Naked Statistics: Stripping the Dread from the Data" by Charles Wheelan is a great choice. It explains everything with examples, making it super easy to read.

was gonna say the same

I thought "Intuitive Biostatistics: A Nonmathematical Guide to Statistical Thinking" combined with "PDQ Statistics" did okay. Way better than the awful instructor textbook taught as an intro to higher-level stats with R and S-Plus, and a useful supplement to the basic 101-102 level applied statistics textbook.

But probably the most useful thing was a college course where we implemented all the 101 & 102 level statistics algorithms in Excel, so you could see precisely what it was doing.

I don’t know about books, but this playlist was a good primer:

https://youtube.com/playlist?list=PL8dPuuaLjXtNM_Y-bUAhblSAd...

I'm working on a stats book right now. You can check out the notebooks + exercises from it here: https://nobsstats.com/

In particular, you might want to start with this 4-part overview, which comes with video lectures: https://nobsstats.com/stats_overview/README.html

I hope to finish the book by the end of this summer (the book itself won't be free, but all the notebooks and additional exercises will be free online at nobsstats.com)

If you're looking for other sources, you can check out this google document where I collect the best STATS101 learning resources: https://docs.google.com/document/d/1GWyuNC4qCL5ecYSoY6GxvuhO...

Good luck with your learning... it's not an easy subject (lots of historical baggage), but it's super important stuff.

I liked and recommend - Statistics Unplugged by Sally Caldwell

Elementary Probability by Stirzaker is my favorite intro.

Exploratory Data Analysis (Pearson Modern Classic) by John W. Tukey

Nothing beats ISLR: https://www.statlearning.com/

How is ISLR better?