[scipy.md] Update np.random → Generator API

[Chihiro2000GitHub]

Summary

This PR updates lectures/scipy.md as part of the NumPy random API migration described in QuantEcon/meta#299.

The changes are limited to the following:

• Replace np.random.beta(...) with rng = np.random.default_rng() / rng.beta(...)
• Update the surrounding wording: "functions" → "tools" to avoid implying module-level functions
• Replace np.random.randn(...) with rng.standard_normal(...) in "12.3.3. Other Goodies in scipy.stats"
• Replace np.random.randn(...) with rng.standard_normal(...) in the Monte Carlo exercise solution (Exercise 12.3)

Each code block defines its own rng locally. The exercise solution block remains self-contained.
No fixed seed is introduced, as the original lecture did not use one.
No Numba-related code was present in this file.

Hi @mmcky and @HumphreyYang, I'd be grateful if you could take a look when you have time.

[github-actions]

🚀 Deployed on https://69fd9e7a14fbc5961e979451--epic-agnesi-957267.netlify.app

[jstac]

Many thanks @Chihiro2000GitHub , this looks good to me.

[HumphreyYang]

Many thanks @jstac and @Chihiro2000GitHub, just one very minor suggestion!

[HumphreyYang]

I remember the convention was to use a single rng for the main text and separate ones in solution blocks (see this PR discussion). According to that, I think we can reuse the rng on line 110 here.

[Chihiro2000GitHub]

Thanks for pointing this out, @HumphreyYang! I had missed that convention.

I’ve removed the additional rng definition on line 192 so that the main text reuses the existing rng from line 110.

[mmcky]

Thanks @Chihiro2000GitHub, @HumphreyYang and @jstac

[mmcky]

✅ Translation sync completed (zh-cn)

Target repo: QuantEcon/lecture-python-programming.zh-cn
Translation PR: QuantEcon/lecture-python-programming.zh-cn#63
Files synced (1):

• lectures/scipy.md

[mmcky]

✅ Translation sync completed (fa)

Target repo: QuantEcon/lecture-python-programming.fa
Translation PR: QuantEcon/lecture-python-programming.fa#120
Files synced (1):

• lectures/scipy.md