test: migrate stats/base/dists/bernoulli/mean to ULP-base assertions

[AryanSharma48]

Resolves a part of #11352 .

Description

What is the purpose of this pull request?

This pull request:

• migrates test/test.js and test/test.native.js of stats/base/dists/bernoulli/mean from relative-tolerance (EPS-based) assertions to ULP-difference assertions via @stdlib/assert/is-almost-same-value.
• replaces the if ( y === expected[i] ) {...} else { delta = abs(...); tol = 1.0*EPS*abs(...); t.ok( delta <= tol, ... ) } branch with t.strictEqual( isAlmostSameValue( y, expected[ i ], 1 ), true, 'returns expected value' ).
• removes the now-unused abs and EPS requires.
• the ULP bound was set to 1 by measuring the actual ULP difference between mean() output and the fixture-expected values across all 1000 fixtures; the maximum observed difference was within 1 ULP (the implementation is a simple identity computation returning p, which reproduces the Julia fixture values), so the ULP bound is set to 1. This mirrors the existing convention used for other simple-formula distribution functions in this codebase. The full suite (1007 assertions per implementation) was run to confirm deterministic results.

Related Issues

Does this pull request have any related issues?

This pull request has the following related issues:

• [RFC]: Migrate math/base/special packages from relative tolerance testing to ULP difference testing (tracking issue) #11352

Questions

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No.

Other

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No.

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• Read, understood, and followed the contributing guidelines.

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Coverage Report

Package	Statements	Branches	Functions	Lines
stats/base/dists/bernoulli/mean	$\\color{green}165/165$ $\\color{green}+100.00\\%$	$\\color{green}9/9$ $\\color{green}+100.00\\%$	$\\color{green}2/2$ $\\color{green}+100.00\\%$	$\\color{green}165/165$ $\\color{green}+100.00\\%$

The above coverage report was generated for the changes in this PR.