Julia cookbook still relevant? sample statistical analyses sessions?


#1

[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=",")
print(summary(d))
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.

regards,

/iaw


#2

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


#3

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.


#4

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.

regards,

/iaw