Hacker News Reader

Comment by dragandj | Hacker News Reader

The problem with these kind of extremely short texts is that they jump into explaining technical concepts without even mentioning basic things such as random variable for example.

Then, readers learn that statistics is about applying a few summing and averaging procedures, and trust the numbers they get as a result.

View on HN

I totally agree. It's much better to start with probability and then move to statistics. It gives both a foundation and the motivation for statistics.

Indeed, and I think Python could be great for learning about probability too. It comes with an endless supply of random numbers. ;-)

Anyone have any recommendations on where to start? In particular, I’ve been looking for a good book on probability.

Jaynes is the usual 'standard' probability text, and it's well written and not too dry. It's mathsy though.

William Bolstad - Introduction to Bayesian Statistics

Or E.T. Jaynes - Probability Theory, The Logic of Science (but this one is much more detailed and has lots of philosophy)

Or Ian Hacking - An Introduction to Probability and Inductive Logic (this is the light approach written for philosophy students)

I like Norvig's Jupyter notebook on Probability using Python.

http://nbviewer.jupyter.org/url/norvig.com/ipython/Probabili...

I recommend Think Stats by Allen Downey http://greenteapress.com/thinkstats/

I'll be posting a separate blog post about probability soon. Anyway, thanks for the suggestion.

Reply on news.ycombinator.com