The Model Thinker is also an excellent book! It's more mathematical models, but if you understand the intuitions behind the models then they are a great additional to your thinking tools.

For me, this was also the most interesting course. But I don't think you can still access it (I tried a couple of months ago to revisit it).
But Scott Page also has a book out on the topic "The Model Thinker", which covers most of the course.

* Poor Charlie's Almanack: The Wit and Wisdom of Charles T. Munger

* Seeking Wisdom: From Darwin to Munger

* The Model Thinker: What You Need to Know to Make Data Work for You

* The Great Mental Models

Yes. I was recommended Page's

"The Model Thinker"
https://www.amazon.com/Model-Thinker-What-Need-Know/dp/04650...

when this YC topic popped up. Page's book is sort of a reference book, something you use periodically rather than a beginning-to-end read.

But it does seem that "models" are all the rage currently.

If you like this - Buy and read The Model Thinker.

I'm reading The Model Thinker at the moment. +1

I would recommend Poor Charlie's Almanack by Charlie Munger and these following two books:

The Model Thinker: What You Need to Know to Make Data Work for You by Scott Page

https://www.amazon.com/Model-Thinker-What-Need-Know/dp/04650...
and

The Great Mental Models: General Thinking Concepts by Shane Parrish

https://www.amazon.com/Great-Mental-Models-Thinking-Concepts...

I have been working on this for a long time now. It helped me achieve small success in writing(My articles gained some attention and ended up publishing a book with packt). I am still a beginner, long way to become a good model thinker.

Here are a few books, I recommend.

1.The Great Mental Models : General Thinking Concepts (Beginner Level)

2.Super Thinking (Intermediate)

3.The Model Thinker (Intermediate-Advanced, you can also take the coursera MOOC "Model Thinking" by the same author)

I am also working on a tool to assit people in thinking with models. If anyone is interested to try out the beta, you can signup here. https://forms.gle/xn9mESKZwUMD2y6RA I am hoping to release it next week.

Here are a few screenshots of the tool I am building. (Note: It's in MVP stage, not a finished product)

https://imgur.com/Jzxw4uz

https://imgur.com/XhiVJQM

The book is designed to support an introductory class on systems - eg a 100 level or first year class. It's a little more technical than you might find in a typical gen-ed quantitative reasoning class, but the material is presented in a way that I think would be approachable from a STEM or non-STEM career emphasis. I trained as an engineer, so I could be overstating that... There is a pedagogical library, pyCX [0]. Overall, I like the design of the book, but would say the intended audience is someone relatively early on their analytic journey and may not serve the interests of the HN reader well.

It has a much broader perspective than Allen Downey's "Think Complexity" [1], which is discrete systems (computational systems) focussed. Maybe you could think about Downey's book is a non mathematical approach to algorithms.

Scott E Page's book "The Model Thinker" is more mathematical, at an undergrad engineering level, and is more of a survey of models than a taxonomic overview of systems modeling, which is what Sayama's [2] book, above, offers. A thesis of Page's book is that there can be many ways to model a problem, and multiple models help.

[0] https://github.com/hsayama/PyCX
[1] http://www.allendowney.com/wp/books/
[2] http://bingweb.binghamton.edu/~sayama/

I read The Model Thinker some time last year. It includes a chapter on the SIR model used in epidemiology. The book states the basic mathematical model for working out how much of the population needs to be immune before 'herd immunity' is achieved is (R0 - 1)/R0.

I have heard R0 estimated around 4. So, technically you would need 3/4 of the population to be immune. The result of this being that R_t drops below 1 thus no longer becomes an epidemic and eventually either disappears or becomes seasonal.