I had a classic Bayesian statistical education throughout my undergraduate and grad years and I’ve come to conclude that the plethora of books offered are pretty bad.

For me personally statistics is intuitive if illustrated properly. A great example is https://seeing-theory.brown.edu/

I was wondering whether it would make sense to turn the intuitions behind statistics into a book. Would anyone read it? Do people still read stats books or would it be mostly a waste of effort? If you wanted to teach/help people understand statistics, what resources would you consider?

A long time ago, I took a "statistics for engineers" class in order to graduate. I slept through most of the classes. It sucked, and 70 percent of it was just "distribution of the week." It did not help that homework was optional for half of it.

At some point in my professional career I started reading non-fiction books and even bought a used statistics textbook for 10 bucks on abebooks. I didn't end up actually reading it until 12 years later during the COVID lockdown. I ended up shooting for 10 pages a day, 7 days a week. If those 10 pages included review exercises, it would be a long night.

Could just be the right book at the right time, but this one really helped me understand stuff beyond the normal HS math stuff, like RMS-error, calculating correlation, the difference between standard error and standard deviation, the relationship between sample size and standard error, t-tests, and chi-squared. Working as an SRE/release engineer, this stuff really helped me overcome a lot of _bad_ canary data analysis my predecessors had constructed.

That book was the 3rd edition of Statistics by Freedman et al.[1] One thing I want to complement was getting the pedagogy right. Most chapters have strong narrative hooks, several "check your knowledge" problems, review exercises, and post chapter bullet points to assist with spaced repetition. There's even a series of "special" review exercises covering entire sections of the book, ie exams.

For the HN crowd I should also probably note that the book is almost entirely non-bayesian and not intended to prepare readers for further coursework. You will not learn normal phraseology like "IID," "random variable" or "kernel".

[1]: https://www.amazon.com/dp/B00SLB5Q72?lv=shuf&channelId=520&p...

My personal opinion is that statistics textbooks usually come from a prescriptive perspective, and that makes it challenging for the reader to get visceral intuition for what is actually going on. Any reader would be far better off just visualizing the damn distribution / samples and using reasonable judgement, instead of implicitly assuming a Gaussians distribution and blindly memorizing tests / formulae. Making the distributions explicit allows us to model them and get an intuition for what the samples are telling us. I would whole-heartedly recommend the Model based machine learning book to anyone (online version is free) https://mbmlbook.com/

Yes surely. I like ML, >D>S and such but lacking in stats background I wishh I had.

No idea about statistics, but in most physict courses in my university, they recomend 3 books:

1) The main book, that has a complete explanation and is well ordered. It's for learning.

2) Tha Landau book, that is super short and hard. It's only to check you didn't miss any important formula or topic.

3) There Feynman book, that is anassorted colection of fairytales for physicist. It's a pleasure to read it but you must already read 1 to understand it.

4) The Shaum book, that is almost a colection of exercices. Some people hate it. Some people love it. I like it as a companion to theother books.

I guess you are complaining that 1 is boring and want to write 3. It's a good idea, but it's harder than expected.

Even if I would not read it back to back on release, it would be a pleasure to have a reliable and citable reference on hand. Whenever I stumble upon new complex problems, outside of the regular, often fairly repetitive statistical questions of my field, I need to rely on many searches and LLM queries to find my answer. I wonder if a book could actually replace all that, but it would be my first place to check.

How would it overlap or differ from 'Statistical Rethinking'?

This is widely regarded as the most accessible intro textbook to Bayesian statistics.

https://xcelab.net/rm/

Yes, I’d read it.

But beware of opinions.

Don’t let people put you down, especially here in HN, where people are perceived to smart. Smart doesn’t equal sensible or unbiased.

Many books are written to scratch the itch of the author. Just like an open source project. It is a work of love.

Definitely there’s an interest for visual pedagogical content. However a book nowadays may not be the most effective way to reach a wider audience, instead of a video or an interactive website. I guess that combining these other media may help you reach more people to get interested in the book.

Another exemple of a successful visual pedagogical content is: https://www.byhand.ai/

I'm a nerd and do a lot of stats for my job and I would not read a statistics textbook.

I read a lot of informational things, but math / stats / software has always felt like an area where a book is just the wrong format.

If I were you I'd make an interactive website like SQLZoo or a video series like StatQuest.

Those are educational formats that really clicked with me for whatever reason.

Having also studied statistics in university (undergrad), something I kept running into is that you can't really unlock the intuition for many concepts without taking more advanced courses. For example, degrees of freedom shows up as early as AP Statistics, but even a non-rigorous visual explanation of it leans on linear algebra, which most students don't see until much later.

I think more resources like seeing-theory would be great since stats books are almost universally dry (Blitzstein being a notable exception), but I'm not sure how easily more advanced concepts lend themselves to visual explanation in a way that's digestible for a non-stats person.

I took my first statistics class as an evening course, before going to graduate school, and 90% of the work involved doing hand calculations, avg., variance, std. dev., z-scores, t-tests, etc. And I think that gave me a strong grasp of those fundamentals.

If you could do something similar for bayesian statistics I think that would be useful, but not necessarily popular.

Aren't a zillion statistics books out there already? Yes I've been wanting to read one, and Wikipedia also has lots of good statistics articles. I've been wanting to work through Freedman and Pisani's book but you know how it goes. It's supposed to be excellent.

I would at least investigate it. I have purchased and read statistics books recently. Mostly the old classics by R.A. Fisher and D.R. Cox and etc, I have a copy of Handbook 91 by Mary Natrella. My questions are pretty simple. I like the "worked examples" approach in Handbook 91.

I have some statistic book in paper, trying to solve some lemmas from time to time, so I will not read any slop.

Not sure I'd read it as-written. But I'd love a statistics book whereby the chapters are real case studies. I personally learn best when I can apply new theory to a tangible problem (not just an example problem that's been reduced to almost nothing).

However going the 'visual' route might be enough for me to pick it up.

Yes, with the caveat that someone else with knowledge in the field has to recommend it to me. Partner up with someone who teaches statistics.

https://stewartschultz.com/statistics/books/Statistics_Terri...

I would! If you are thinking to write one, do it!

Such a bizarre question. Many, many people have read statistics textbooks.

Can you write one that's more worth reading than the standard ones? Don't answer that question, just prove it.

Yes, I love it and would do so

I would read it

It depends on what parts of statistics is being taught and the application of each of the leanings and how it relates to the real world.

More generally, I would buy a statistics if it is linked to today's interesting technological breakthroughs and also if it comes as a distilled version for beginners.

Yes foundations of agnostic statistics and all of statistics

I’m weird. I read textbooks and instruction manuals. I read incredibly fast though, so it fits nicely. There’s always some deeper learning to be gained in those pages.

Good luck if you do this.

Probably.

Yes, there is always a need for another "intuitive statistics" book.

However the link you have provided is not the way; it is low on content and high on pretty distractions. Use all sorts of diagrams and graphs primarily, with animations only where required. The key is to always relate to something in the real world so one can see its actual relevance. Also tie it back to other fields of mathematics so one can see how they all come together.

A good example to study is How to Measure Anything: Finding the Value of Intangibles in Business by Douglas Hubbard. Detailed review at - https://www.lesswrong.com/posts/ybYBCK9D7MZCcdArB/how-to-mea...

And of course Nassim Taleb's works are a good source of inspiration. Here is a great video summarizing Taleb's ideas nicely Pareto, Power Laws, and Fat Tails - https://www.youtube.com/watch?v=Wcqt49dXtm8