I came across a 2012 question that had a very good discussion about Julia as an alternative to R / Python for various types of Statistical Work. 

[Here lies the original Question from 2012 about Julia's promise](https://stats.stackexchange.com/questions/25672/does-julia-have-any-hope-of-sticking-in-the-statistical-community "Here lies the original Question")

Unfortunately Julia was very new back then & the toolkits needed for statistical work were somewhat primitive. Bugs were being ironed out. Distributions were difficult to install. Et cetera. 

Someone had a very apt comment on that question:

> 
> This said, it'll be 5 years before this question could possibly be
>  answered in hindsight. As of right now, Julia lacks the following
>  critical aspects of a statistical programming system that could
>  compete with R for day-to-day users:
> 
> 
> 

That was in 2012. Now that it's 2015 and three years have passed, I was wondering how people think Julia has done? 

Is there a richer body of experience with the language itself & the overall Julia ecosystem? I would love to know. 

Specifically:

1. Would you advise any new users of statistical tools to learn Julia over R?
2. What sort of Statistics use-cases would you advise someone to use Julia in ?
3. If R is slow at a certain task does it make sense to switch to Julia or Python?

Note: First posted June 14 2015.