# Convince me to use Julia

**URL:** https://discourse.julialang.org/t/convince-me-to-use-julia/38635
**Category:** Teaching & Outreach
**Created:** [May 2, 2020, 11:20pm UTC](https://discourse.julialang.org/t/convince-me-to-use-julia/38635 "2020-05-02T23:20:28Z")
**Posts on this page:** 1
**Showing post:** 18

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### Author: ![jonathanBieler](https://avatars.discourse-cdn.com/v4/letter/j/82dd89/32.png) [@jonathanBieler](https://discourse.julialang.org/u/jonathanBieler)
#### Post date: [May 5, 2020, 11:53am UTC](https://discourse.julialang.org/t/convince-me-to-use-julia/38635/18 "2020-05-05T11:53:40Z")

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I you like R and statistics, I have some examples where Julia is better (in my opinion) here :

> [@Designated Target Audience of Julia 1.0?](https://discourse.julialang.org/t/designated-target-audience-of-julia-1-0/11804/21):
>
> I’m not very well-versed in R but I find it quite horrible for statistics, for example in Julia if you want to compute the pdf of a Normal distribution with parameters (μ,σ) at value x you do : pdf(Normal(μ,σ),x) In R you do: dnorm(x,μ,σ) If you want to truncated Normal between zero and one you do: pdf(Truncated(Normal(μ,σ),0,1),x) In R you do: google for a package ... dtrunc(x, spec="norm", a=0, b=1, mean=μ, sd=σ) If you want a mixture of two Gaussians: MixtureModel([Normal(μ1,σ1), Nor…

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