# Output distribution of rand(Float32) and rand(Float64), thread 2

**URL:** <https://discourse.julialang.org/t/output-distribution-of-rand-float32-and-rand-float64-thread-2/105184>\
**Category:** Internals & Design\
**Tags:** float, random\
**Created:** [October 19, 2023, 1:10pm UTC](https://discourse.julialang.org/t/output-distribution-of-rand-float32-and-rand-float64-thread-2/105184 "2023-10-19T13:10:07Z")\
**Posts on this page:** 1\
**Showing post:** 41

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**Author:** ![mbauman](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/mbauman/32/31082_2.png) [@mbauman](https://discourse.julialang.org/u/mbauman)\
**Post date:** [October 23, 2023, 5:10pm UTC](https://discourse.julialang.org/t/output-distribution-of-rand-float32-and-rand-float64-thread-2/105184/41 "2023-10-23T17:10:30Z")

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Personally, I’ve always been scared (perhaps unreasonably so) to muck around with `rand()`'s output. I’m not sure where this trepidation came from, but it predates Julia — I remember fretting about hand-written re-computations of random distributions in Matlab and C in the 00s. I don’t think it really matter whether the output distribution is evenly spaced or if it’s logarithmic; either way, floating point challenges aren’t too far away.

In my view, getting random distributions right is the work of magicians — along the same lines as getting encryption right is (if not even more fundamental). To wit, the straw-stuffed implementation [in the first thread](https://discourse.julialang.org/t/output-distribution-of-rand/12192) on this isn’t generating a correct uniform distribution AFAICS — so we don’t have a solid view on what such a performance impact would be, but it’ll certainly be worse than what’s there.

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