Yeah, it's a tough call. I can see R being very useful, but ChucK is way more fun. C just seems like a book that needs to be written before the "learning C sucks" situation gets worse.

For what it's worth, my vote would be for Learn C The Hard Way. Not having learned C in any formal setting and coming from a background of mainly interpreted languages, I've found it quite difficult to determine reliable, up to date resources for learning C. It's not that there's none around obviously, it's just hard to know which stuff to go with and hard to find something in between complete n00b and full master, which is what I'd be hoping for.

"hard to find something in between complete n00b and full master" - My theory is that the best technical books or books for learning are the "intermediate" ones.

There are usually a ton of acceptable beginner's books and then very specialized and complex books but very few good "intermediate" books like the favorites:

- TCP/IP ilustrated - Perl Camel book - R&K C book - Silman's groundbreaking chess books - Harrington's groundbreaking poker books

My vote would be for C, but any one of those books would be a great way to learn something new.

Please cover GDB and ctags in your LCTHW book.

I'd love to see the R book to a) actually become familiar with it and b) because it'll also provide a refresher to some theory I've unfortunately forgotten. Plus, you're due for some more posts about the importance of that stuff for programmers. :)

I agree with all parts of that statement. A contemporary C book (as applied to servers etc.) would be much needed, before the world turns into a morass of webdev frontend programmers…

by the way - I started the python book this week (I'm up to ex42). It's great, thanks for putting all the effort into teaching.

Putting in a vote for ChucK.

I'll vote for LCTHW

Yeah, but R is all caught up in a stats education -- and I think that's much harder to cover in a single book. Just my .02.

If people are looking for a broad overview of statistical stuff -- what's a t test, a sampling distribution, a regression, anova, variance, glm family, etc, I'd recommend this unfortunately very expensive book: http://www.amazon.com/Statistical-Sleuth-Course-Methods-Anal...

It's very applied with subject oriented chapters, eg what is regression? What about regression where my dep var is counts? A probability? With correlations in the design matrix? It's not perfect, but for self learning of stats, it's the best thing I know of.