# 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:** 369

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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: [November 2, 2023, 2:51pm UTC](https://discourse.julialang.org/t/output-distribution-of-rand-float32-and-rand-float64-thread-2/105184/369 "2023-11-02T14:51:54Z")

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Personally, I’m approaching this from a documentation standpoint. Our current docs say:

> concrete floating point types sample from [0, 1)

This should say more, even with the status quo implementations. Perhaps something like:

> The types `Float16`, `Float32`, and `Float64` return values in [0, 1) as though a random variable were drawn from a theoretically ideal uniform distribution and then rounded down to the previous multiple of `eps(T)/2` (this value may decrease in the future).

I’d **want** to be able to say:

> The types `Float16`, `Float32`, and `Float64` return values in [0, 1) as though a random variable were drawn from a theoretically ideal uniform distribution and then rounded down to the previous floating point number.

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