Julia cookbook still relevant? sample statistical analyses sessions?

[1] the coverage of julia’s cookbook by jalem rohit looks nice, but it is from mid-2016 and I know that julia has recently changed quite a bit. is it still recommendable?

[2] I am looking for a variety of short statistical analysis starter sessions for my students (and myself). as an example, my first task is

d <- read.csv( gzfile("a.csv.gz"), sep=",")
m <-  lm( d[,1] ~ abc, data=d )  ## abc is a column in d
print( coef( m ) )
d <- within(d, r <- resids( m ))
plot( d$abc, d$r )
write.csv( pipe( "bzip -c > a2.csv.gz" ) )

I asked questions like this before, but the answers were complex and julia is now so changed that I do not know what the right approach is. (and I don’t want to get my students started doing it wrong; and google still mixes in old julia links aplenty.)

advice appreciated.



The GLM.jl package may be useful for your use case, their README has a set of examples:

Depending on the session, assuming next semester, you could use Julia 0.6.2 and the ecosystem for it. If later than spring or mid way during that semester, I would use Julia 0.7 and the ecosystem for it.

the MFE class will be in Winter 2018, so Jan through Mar. we will leave the choice of version up to our students, but I think we will recommend julia 0.6.2.

pranav bhat (our resident julia expert) and I are creating a wiki, to be public in a week or two at http://julia.cookbook.tips, that will collect all sorts of recipes and will, we hope, complement the official docs and forum. We are planning on working on it quite a lot over the next week. I will post a notice here when we have something share-worthy and when we want to solicit questions about what else we should cover.